Bilingual Teaching Pedagogies in Academic Practice: Embed

American Journal of Humanities and Social Science (AJHSS) Volume 6 2020

1

Bilingual Teaching Pedagogies in Academic Practice Embed

Teaching Approaches

Wenchu Li BaoliQiu Yangjin Zhong

Department of Sericultural Science College of Animal Science South China Agricultural

University PRChina

Abstract

To explore a bilingual course of Insect Physiology and Biochemistry we have in recent years

tried to embed teaching pedagogies such as a flipped classroom that combines brain storming

and ―Six Thinking Hats in undergraduate education Analysis revealed that there are no

significant differences between the final test scores of the classes A revised analysis of

Blooms digital knowledge dimensions showed that the knowledge dimension exhibited

procedure collinearity and Factual negatively affected Meta cognitive in both the Toulminlsquos

practical argument and control groups The addition of ―Six Thinking Hats generated higher

quality and more creative ideas than a flipped classroom alone We confirmed that the

participants under the yellow and green hats generated higher quality ideas than that of red hats

in the creative and innovative thinking model Partial least squares structural equation

modeling analysis of the effect of teaching confirmed the reflective model and data at

satisfactory validity and suggested that essential teaching procedures have a nearly equal

influence on the higher-order construction of brainstorming and innovative thinking Skill has

a strong effect on brainstorming Similarly we found that brainstorming has a strong effect on

innovative thinking However studentslsquo satisfaction is principally affected by innovative

thinking but not by brainstorming

Keywords Flipped classroom brainstorming innovative thinking Six Thinking Hats

Blooms digital knowledge dimension PLS-SEM

1 Introduction

Accompanied by the rapid development of a modern economy and society and the

instantaneous changes of the international interflow of thinking and brainstorming (BRM) in

every scientific field the demands for talented and unique individuals will largely exceed the

supply In light of this point academic education presents diversification of wisdom and

knowledge Bilingual teaching has become a new means to improve the educational qualities


2

of undergraduate and postgraduate students Bilingual teaching promotes reform in education

and its system for economic globalization reflects a higher quality of education and updated

awareness of innovation improves teaching practices accelerates teaching methodologies

implements teaching measures and maximizes teaching achievements Furthermore bilingual

teaching optimizes the knowledge structure of personnel and drives education toward a more

elevated hierarchy

This paper focuses on the popularized flipped classroom BRM and ―Six Thinking Hats aims

to explore the effects of embedded techniques of teaching and estimates the quality of different

pedagogies in academic education (Fig1)

Fig 1 An illustration of the executable training ideas of the course Insect Physiology and Biochemistry

2 Theoretic Background

The pedagogies of teachers applied in the classroom leads to the process of teaching described

as ―pedagogies are dependent on teacherlsquos personalities and preferences Some investigators

focused on beliefs and suggested that the beliefs of self-efficiency of both teachers and students

can assist learners in improving their language learning (Achu and Ehizuelen 2015 Liu 2018

Menon and Sadler 2018) However increasing numbers of educational specialists suggest that

students should take charge of the learning process and teachers act just as learning services

(Swacha 2017 Jagla and Tice 2019) This view is the concept of a ―flipped classroom

(Reidsema 2017) and most educators consider this to be a type of blended learning

(Abeysekera and Dawson 2015) The characteristics of blended learning combine or mix


3

modes of web-based technology various pedagogical approaches (constructivism

behaviorism and cognitivism) any form of instructional technology (videotapes CD-ROMs

web-based training and films) with face-to-face instructor-led training and instructional

technology with actual job tasks (Driscoll 2002) A flipped classroom not only is based on

blended learning but also requires students to engage in or complete preliminary learning

online in preparation for a structurally aligned learning activity rather than by attending a

traditional lecture or blended learning and this approach has become an attractive proposition

In flipping higher education the teaching process will obviously be very challenging for the

teachers when they are faced with a room full of students who are prepared for intellectual

discussion (Reidsema et al 2017) Therefore a flipped classroom requires more professional

and interesting topic preparation when teachers step into the classroom The pedagogy in the

classroom encourages all students to freely express their own ideas and even to organize and

lead the teaching process In addition by carefully exposing students to important concepts and

knowledge points in the curriculum the effectiveness of teaching in a flipped classroom might

be better than other student-centered learning theories (Betihavas et al 2016) such as

attractive learning (Deslauriers et al 2001) and peer learning (Mazur 1997)The advantages of

flipped classrooms have been frequently reported to be the improvement of student learning

performance (Goumlkccedile and Murat 2018)

In a flipped classroom heuristic teaching (Bridgham 1970) and problem-based learning

(Barrows 1986) are essential elements Heuristic teaching is a teaching process of revealing

what is hidden in phenomena According to Bridgham (1970) heuristic teaching involves

addressing problems that are indeed problems and a critical aspect of a science subject is that

selected hypotheses promote active doubt until the hypotheses are sufficiently justified

However the questions that arise from science cannot only be addressed through a

problem-solving scientific project The existing theories techniques and conceptual

frameworks are useful as a guide to understand new phenomena In this way a line of inquiry

brings students to the cutting edge of modern biology

In any form of pedagogy a dominant source of content is teaching materials that promote and

guide studentslsquo creative and thinking skills (Alkhaldi and Oshchepkova 2018) Osborn (1953)

proposed that BRM is usually conducted by rules that include avoiding criticism saying or

writing all the things that come to mind attempting to generate many ideas without paying

attention to quality and trying to develop and combine ideas A new BRM principle was

developed on the generation of high-quality creative ideas in an individual-group-individual

(I-G-I) procedure (Rossiter and Lilien 1994) The nominal group showed advantages in

specialized problems but the BRM group exploited the diversity of competence of its

participants to attain better solutions to cross-functional problems (Kavadias and summer

2009)

More interestingly De Bonolsquos ―Six Thinking Hats is beneficial for developing the creativity

of learners and can be applied in science and technology classes (Orphan and Kadar 2014)

The Six- Thinking Hats model creates six parallel thinking models which correspond to the


4

primary thought modes of objective subjective critical and creative thinking within a

comprehensive framework that allows the thinker to direct attention to the desired thinking

mode The BRM and Six Thinking Hats theory and practice instructs many teachers to utilize

them in academic education (Khine and Lourdusamy 2003)

3 Methods

The main study method is a quasi-experimental design with a control trial On the subject

course and synchronous matching experiment sixty-nine undergraduate students in different

grades who enrolled in the College of Animal Science at South China Agricultural University

participated in the project The participants were randomly divided into three large groups

based on classes and divided into 13 small groups with 5-6 students each who responded to the

questionnaire in a flipped classroom with BRM and ―Six Thinking Hats To construct a

discussion section group I was assigned to search the data information and task items while

group II was assigned to be the control group to only read the textbook and build a basic

conceptual framework of the scientific issues The participants were asked to answer a list of

questions not only to participate in the theoretic class but also to complete the synchronous

insect scientific experiments In general when one group chose to try to prove or illustrate the

theory with information the other group took the opposite position to raise critical views on the

questions Through positive and negative discussions the conceptions and disciplines are more

sufficiently understood by the students themselves In the case of discussing the questions in

detail a flipped classroom heuristic teaching integrating direct instructions with a

problem-based learning approach (Winarno et al 2018) and BRM are frequently used among

the pedagogies

31 Understanding professional vocabulary abilities

Vocabulary learning strategies are typically most studentslsquo favorite aspect and these strategies

use the dictionary and studentslsquo cognitive and meta cognitive memory some students use

determination and guessing from the context Quizzes of vocabulary are always administered

before the class begins Fellow students are divided into couples in a group to play asking and

answering vocabulary games at the English Corner outside the classroom After the course

tests of the professional vocabulary of insect science were conducted in a final examination

The vocabulary scores were analyzed by SPSS statistical software to distinguish the difference

among the classes and grades of students together with their final exam

32 Comprehensive knowledge points

A knowledge point is a basic unit of teaching content and is an indispensable foundation of

teaching activities Structure knowledge points can be parent-child sibling dependence and

the association relationship model (Li 2014) Structure knowledge points might be a

conceptual framework essential knowledge and even a typical case that reflects a scientific

principle Basic principles of Insect Physiology and Biochemistry are scattered and even


5

hidden in the cases or textbook which is the main logic of the curriculum In a synchronous

experiment class students were organized into groups to change the thinking model to initiate

BRM creative and innovative thinking and to discover the knowledge points Some of the

students who prepared before class showed a cheerful countenance when they read the question

in contrast other students struggled to answer the question and needed the guidance of the

teacher or an example to follow from other classmates in the groups To estimate the degree of

understood knowledge points we usually draw an outline of the question and the epigenetic

data or phenomena of a silkworm for example Through a group discussion in the BRM style

students can develop their creative thinking abilities that encourage their expression of ideas

In this study the Daily Performance scores are calculated according to the Educational

Administration Provisions of the university These scores include 5 for class attendance 20

for quizzes in the classroom 25 for homework and 50 for the final exam A final

closed-book examination of the course was administered at the end of the term The

propositional rules included testing the professional vocabulary and the abilities of listening

speaking reading and writing where an English thinking model was emphasized In terms of

the final exam 100 scores were assigned in professional vocabulary with 20 points in the form

of ―Fill in the blank while ―Judgments contained 10 small pieces of knowledge points with 1

point each which were easily conceptually confused in the course Moreover 10 points of

―Comprehensive essays ask the participants to choose one correct answer from five possible

answers to complete the sentence statements after they read short descriptions ―Translation is

usually assigned 20 points and requires students to intertranslate insect science principals

especially frontier achievements in English or Chinese The fifth examination question with

40 points is ―Essay questions which normally contain two or three minor topics The scores

that the students receive are critically calculated depending on the correct degrees of

knowledge points and then an SPSS statistical analysis is conducted to analyze the differences

among the different classes and grades of the students

33 Physical and biochemical insect cases

In the historical insect studies many cases are typical examples of heuristic and

problem-solving methodologies that require creative and innovative thinking The cases

represent advanced studies in the field of insect physiology or biochemistry at the time and the

discoveries still greatly influence future generations For example the French anatomist

Lyonet described a pair of minute organs located within the thorax of caterpillars as

―granulated vessels in 1762 It was unbelievably remarkable as Fleming observed that the

description of such organs had been forgotten for as long as 187 years This description had

been buried in the literature that pertains to insect anatomy until it was rediscovered by various

investigators These organs which are currently known as the ―prothoracic glands are among

the most important endocrine glands in insects Many other insect scientists have achieved

many theoretic innovations based on the careful observation of phenomena The following

examples are similar to golden of clues for insect studies

Huberlsquos discoveries on the mating of queens


6

Morganlsquos work on the chromosome theory of heredity of Dmelanogaster

Malpighilsquos study on the Malpighian tubule system

Wigglesworthlsquos research on the juvenile hormones of insects

Kar von Frischlsquos observations on honey bee dances

Hoffmann et allsquos achievement on insectslsquo innate immunity

Hall et allsquos discoveries of the molecular mechanisms that control the circadian rhythm

Nagasawalsquos discovery of Bombyxin in Bombymori and other scientistslsquo findings of

Bombykal and pheromone binding proteins from this model insect

The pioneering achievements in journals are usually chosen in the form of one or two

short essays such as the discoveries of the Nobel Prizes in physiology and medicine that relate

to the story of autophagy circadian rhythms and innate immunity of insects

Table 1 Flipped-classroom discussion about Huberlsquos discoveries in a revised TPA designation

TPA Code Participants response Score

Claims M Queens are physically inseminated by drones outside the confines of hives 1

Qualifier FPM （1) The queen may live for up to three years or more

（2) Nurse bees set about constructing emergency queen cells after splitting

1

FPM 1

Evidence FPCM

Swammerdam Reacuteaumur Huber and Burnens dissected bees under the

microscope and observations 1

FPM Mating takes place at some distance from the hive 1

Warrants FPM （1) Beelsquos activities within hives

（2) The queenlsquos life cycle and characters including mating behavior

1

FPCM 1

Backings

FPCM

（1) Reacuteaumur and Huber constructed and improved glass walled observation

（2) The queen is fed a larger amount of royal jelly and secretes ―Queen

substances

1

FPCM 1

Rebuttals

FPC

（1) No one had ever witnessed the mating of a queen and drone and many

theories held that queens were ―self-fertile

（2) Other scholars believed that a vapor or miasma fertilized queens

1

FPC 1


7

Note The revised TPA designation comprises 10 factual subjects 6 conceptual items 10

procedural items and 9 metacognitive items M Metacognitive F Factual P Procedural C

Conceptual

The above successful cases are creative and innovative events that could be used for references

and literature-based learning (Henry and McInnes 2017) In a flipped classroom the cases

were meticulously designed and prepared as teaching materials under the guidance of

pedagogies to show the process of creative thinking in a layer-by-layer cocoon-stripping

manner However only an imitate tutorial causelsquos students not to think about innovative

abilities For example ―Huberlsquos discoveries on the mating of queens is a questionnaire

designed according to TPA (Toulmin 2003) as shown in Table 1 and coded with revised TPA

designations The students were divided into 13 groups and each group had a question and

discussed it in the context of the categories The assistants helped to code cross-check and

revise the argumentation to collect the data and to record the scores All students in the groups

who provided sufficient information and fully proved the argument can obtain a high score

The discussion of every item was estimated based on Bloomlsquos digital knowledge dimension

(Bloom et al 1956) and the revised version (Anderson and Krathwohl 2001 Lee et al 2017)

According to Bloomlsquos theory and revised version the taxonomy comprises 6 categories of

objectives from the simplest to the most advanced which are ―Knowledge Comprehension

Application Analysis Synthesis and Evaluation while the revision accordingly proposed a

two-dimensional approach of knowledge dimensions and the cognitive process to map

cognitive development Thus knowledge was classified into four levels ―Factual Conceptual

Procedural and Metacognitive and into six categories of cognitive processes namely

Remember Understand Apply Analyze Evaluate and Create

34 BRM experiment

BRM techniques have been widely used in higher education to develop individual

studentslsquo creative and innovative thinking Given the experiment of the ―Determination of

transaminase activity in the silk glands of Bombyxmori we tried the procedures in an I-G-I

model

In this experiment we aimed to lead the studentlsquos touse their imaginations in a heuristic

manner and to provide their views on a specific question from different angles As expected

before the class different answers emerged at different levels and presented a great variety of

ideas because BRM does not exclude strange erroneous thoughts or misconceptions The ideas

not described in the ―Insect Physiological and Biochemical Experimental Guidance are

viewed as creative thinking For instance if the reaction is conducted under inorganic

conditions the enzymes on other substrates are fixed etc and the experimental procedures

could be improved At the end of the BRM section the students were asked to individually rank

the operational experiment procedures of the class at the level of Original Flexible Persistence

and Quality (Nijstad et al 2010) on a 5-point Likert-type scale (Likert 1932 Goumlccedilmen and

Coşkunb 2019) that ranged from 0-4for each instruction question


8

35 Creative and innovative thinking

Six Thinking Hats helped the group to examine problems from different perspectives one at

a time to avoid confusion from too many angles that would crowd thinking The students in a

group practiced parallel thinking in which everyone thinks about the same question with the

same condition and they face the same challenge However real creative and innovative

thinking could be evaluated with the number of Original Flexible Persistence and Quality

ideas and analyzed according to the categories and subcategories of the ideas which points to

cognitive flexibility and persistence

The target items regarding ―DNA extraction from silkworm and mulberry were required to be

completed in 20 min and were assigned to Group I as shown in Table 2 while Group II was

assigned to be the nominal group as the control to discuss the question in a flipped classroom

manner The ―hat color was randomly assigned to the students and the color required the

students to focus on creative generative thinking and to facilitate thinking concerning the

corresponding model Flexible persistent and quality ideas were extracted from each

participant and evaluated There are 20 items with different degrees of difficulty which are

assigned 1-2 points each and the average scores were collected in the group Each ―hat sums

to 5 points of quality ideas based on the evaluation points of the items that include 1 point

added to their response speed and the total marks were calculated on a 20-point Likert-type

scale that ranged from 0-20

Color Definition Studentslsquo thinking process on the case

Facts figures

and information

Analyze available information of DNA extraction protocol past trends and

try to find more referable information

Emotionsfeelings

hunches intuition

Although it is difficult to decide the same procedures due to specific

species the materials are all in fact eukaryotes

Cautiontruth

judgment critical

Note that some information on the DNA extraction from eukaryotes could

be used in the experiment but what is critical is how to lyse the different

cells of silkworms and mulberries to release DNA and isolate it from

impurities such as proteins and RNA It is also critical to isolate nucleic

acids from proteins A centrifuge is an important piece of equipment in the

experiment

Advantages benefits

savings

The most advantageous method of lysing cells is grinding the materials

under an extremely low temperature to maintain the activities of chemicals

and further incubating the materials in a trypsin solution to lyse the cells

extract the nucleic acids with tris-balanced phenol and chloroform to

remove most proteins precipitate the nucleic acids with prechilled

anhydrous ethanol and remove the RNA with RNase


9

Exploration proposals

creativity and new

ideas

Given the information of DNA extraction the procedures of DNA

extraction are similar to the treatment of samples and isolation Creative

experiments in sericulture which simultaneously involve insect and plant

science in the same class

Control organizing The thinking process focuses on DNA extraction with different materials

This process is useful for students who major in sericulture

36 Research on the teaching and learning effects of the course

After the course was finished the students were asked to complete an electronic answer sheet

that includes40 questions about the course using 7 points of Likert-type scale coding from 1-7

The contents are categorized by eight contents classified into affective and cognitive

components including in-class activity (ICA) out-of-class activity (OCA) feedback (FBK

ie homework exercises and stage examinations) and performing technology (TEC) the

other four items include knowledge (KNL) skill (SKL) innovative thinking (ITK) and

satisfaction (SAT) By hypothesizing that ICA OCA FBK and TEC we performed daily in

teaching processes basically reflected the studentslsquo KNL and SKL the project focused on

BRM and ITK as the main targets which finally influenced the SAT of the participants As

there was only a small sample collection that did not impose distributional assumptions on the

data partial least squares structural equation modeling (PLS-SEM) is particularly used for

exploratory research settings The measurement scale referred to the 4D_FLIPPED

measurement model (Murillo et al 2019)By running SPSS software the standard factor

loadings (λ) and Cronbachlsquos α values were evaluated Then the average variance extracted

(AVE) and composite reliability index (CRI) can be calculated with the following formulas

119860119881119864 = 120582119894119899119894=1

2119899 (Sarstedt et al 2019) andCRI =

( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+( (120579119894 )119899

119894=1 )

(Bagozzi and Yi 1988) or 119862119877119868 =( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+119899minus (120582119894 )119899

119894=12 (Biemer et al 2009)

Where n is the number of variables and θi is the standard error variance

After the above indexes have been confirmed as reliable and valid the structure model should

be constructed Considering the characters of our performance and data collection the

measurement model should be reflective of a specified model that uses a correlation weight to

estimate the PLS path ie reflective-reflective and formative-reflective types (Fig2) The

data analysis steps were followed by Murillo et al (2019) and Sastedt et al (2019) by using

SPSS and manually computing According to the measurement structure model BRM can be

conceptualized as a higher-order construct that comprises the two lower-order components of

KNL and SKL Therefore we construct a reflective-reflective type of higher-order construct

By manually computing the data the reliability and validity of the statistical analysis and

discriminate validity were calculated by the formula described by Sastedt et al (2019)


10

Fig 2 Original construct model

4 Results

41 Professional vocabulary and comprehensive knowledge points

The results of the closed-book examination (Figs3-7) indicated that nearly almost all students

understood the required professional vocabularies however they also revealed that no one

completed the blanks perfectly and most students scored 6 to 14 points at the middle level The

students also did not clearly understand the insect science principals and concepts as more than

15 students scored lower than 50 and few students had positive thoughts on the knowledge

points This result was further demonstrated by the third topic of the exam namely the

comprehension part The largest portion of students scored at the middle range from 6-9 points

but unlike the judgment topic some students answered the questions perfectly This result

reflects a great improvement of the topic of the intertranslation title The students are

accustomed to thinking of the words and sentences in the English model and most of these

students gained 14~19 points Of course it seemed difficult to obtain fully correct answers

The essay questions mainly evaluated more comprehension abilities which requires the

students grasp the conceptual framework the principals of insect science and innovative

thinking Some of the students achieved more than 50 of the scores Furthermore eliminating

the low degree of difficulty of test paper in every grade the scores are statistically analyzed by

SPSS A paired samples t test analysis revealed that there are no significant differences

between the classes and grades (at Plt005) Table 3 presents the results of the t-tests on the


11

total scores that reflect that the tests are fair critical and they represent an understanding of

insect science after the course is completed

Fig 3 Score distributions in the Professional Vocabulary test with 20 points on the final exam

Fig 4 Score distributions in the Judgment test with 10 points on final exam


12

Fig 5 Studentslsquo achievement in the Comprehension test with 10 points on the final exam

Fig 6 Student numbers and their scope in the Intertranslation test with 20 points on the final

exam


13

Fig 7 The effects of the students learning on the Essay Questions test with 40 points on the

final exam

Table 3 Paired samples t test of the total marks at the end of the terms

Paired Differences

t df P Mean SD Std Error Mean

Class I - Class II -1650 11198 250397 -659 19 518ns

Class III -Class I -6770 22543 470043 -1440 22 164 ns

Class II - Class III 9235 20863 466502 1980 19 062 ns

Note ns represent no significant levels at Plt 005

42 Flipped classroom discussion based on revised TPA

The flipped classroom discussion in the TPA designation comprised 10 factual subjects 6

conceptual items 10 procedural items and 9 metacognitive items If students suggested a new

idea to assess the issues such as a demonstration procedure never described before then the

scores were added to the group such as modern technologies such novel ideas included a

DNA footmark testing the activities of special enzymes etc as evidence for procedural proof

and applying factual conceptual procedural and metacognitive strategies to illustrate their

views on the subjects Not creating factual conceptual and metacognitive ideals are marked

zero

First SPSS analysis revealed that the reliability index Cronbachs α of Groups I and II is 0959

and 0957 respectively This finding indicates validity satisfaction The ANOVA showed a

significant difference at Plt 001 in both the individual group correlation coefficients in the

single and average measures Second if Metacognitive was considered the target of conceptual

teaching the collinearity statistics reveal that the variance inflation factor (VIF) of Factual


14

Conceptual and Procedure in Group I are 6930 7900 and 5741 and in Group II they are

11476 8174 and5422 respectively Otherwise the VIF could be estimated by a weighted

least squares analysis where we found the R2 of Groups I and II to be 0884 and 0871

respectively which indicates that the regression of Group I is better than Group II

Interestingly the standardized coefficients β revealed that the Factual negative affects the

Metacognitive in both groups (Factual β = -1654 and -2497 respectively) Third concerning

the cognitive processes the t Test revealed that there are significant differences at P lt 001

among Remember Understand Analyze and Evaluate in the two groups There are no

significant differences between Apply and Create This result indicates that the participants

showed variable abilities to Remember Understand Analyze and Evaluate the knowledge but

weak abilities in applying the knowledge and creating new ways to prove the ideas On the

level of the knowledge dimension the SPSS analysis suggested that there are significant

differences among all cognitive processes at P lt 005 (Table 4) in every learning step of

knowledge The results revealed that all participants have difficulties in proving the conceptual

framework of Huberlsquos discoveries applying the knowledge finding new information and

thinking creatively about the issue

When we compared the scores between the groups by using a paired-sample t test it showed

that there are significant differences between the groups in Remember Understand and

Evaluate at Plt 001 and in Analyze at Plt 005 but there are no significant differences between

the groups in Apply and Create This result indicates that the students who were randomly

divided into different groups and faced the same question might respond differently

Table 4 SPSS analysis of the scores in the discussion with a revised TPA flipped-classroom

Items

Mean SD t P

Group I Group II Group I Group II Group I Group II Group I Group II

Remember 29950 22025 7846 6699 7635 6575 0005 0007

Understand 33925 25650 1986 2009 34171 25533 0000 0000

Apply 2325 4375 0854 4826 5446 1813 0012 167

Analyze 26025 19250 7556 5251 6888 7331 0006 0005

Evaluate 31650 24700 5690 4243 11125 11644 0002 0001

Create 0625 0375 1250 0750 1000 1000 391 391

Note

indicates significant differences at Plt 001 and indicates significant differences at

Plt 005


15

43 BRM experiment

In BRM a conceptual framework could not be renewed and raised by the students however

they performed Flexible Persistence and some Quality ideas well There are significant

differences between the scores of the three classes considering the level of Flexible and

Persistence ideas at Plt 001 but the scores of Quality ideas were at Plt 005 (Table 5)

Table 5 SPSS analysis of the scores in the performance of BRM on ideas and class levels

Mean SD t df P

Original 0000 0000a

Flexible 119333 13317 15521 2 0004

Persistence 70000 6928 17500 2 0003

Quality 36000 6928 9000 2 0012

a t cannot be computed because the standard deviation is 0 represents a significant

difference at Plt 001 represents a significant difference at the 005 level (Plt 005)


To evaluate the thinking effectiveness the scores of Original Flexible Persistence and

Quality ideas regarding the question of ―DNA extraction from animal and plant materials

were recorded according to the studentslsquo performance In terms of the thinking speed there are

significant differences at Plt 005 among the four paired hats ie red hat and yellow hat black

hat and green hat yellow hat and blue hat and yellow hat and control There are no significant

differences between the other thinking hats For convenience in comparisons we calculated the

scores of the students under each hat color (Fig8) and conducted an SPSS analysis The

Pearson correlation between the scores of every hat color is 0866~0993 but it is lower

between the scores of the Six Thinking Hats and the control as they are unrelated The Pearson

correlation between the average scores of the three classes is 0990~0993 which means that

three classes performed the technology in the same manner Quality ideas were generated more

frequently by the yellow color The SPSS analysis showed that there are significant differences

at Plt 001 among the yellow white black blue and control groups Another unusual hat color

is blue because of the few ideas generated but it only drew a conclusion from the other five

thinking hats There are significant differences at Plt 001 between blue and white red black

and yellow Significant differences were still observed at Plt 005 between the control and red

white and black yellow and red and yellow and green hats The results suggested that the Six

-Thinking Hats technology generated higher quality and more creative ideas than the

technology of a flipped classroom alone and it promoted the students to consider the issue


16

more quickly for the group effects The data also showed that there are significant differences

at P lt 001 between white and blue white and the control group and the black and blue hats and

significant differences at P lt 005 between red and black red and blue yellow and blue and

yellow and the control Accordingly the yellow hat plays an important role in the Six Thinking

Hats technology On the other hand the blue hat was the organizer who generated few but

quality ideas that were also crucial to the technology

Fig 8 Comparison of the scores for the number of ideas generated by different hat colors and the control

45 Investigation of the studentsrsquo view on the effects of the course

451 The measurement model

The results of the PLS-SEM techniques analysis based on SPSS and the calculation by

formulas showed that all of the factor loadings were greater than 06 All indicator loadings

were higher than their respective cross loadings which provide further evidence of

discriminate validity The loading values are considered to be acceptable in exploratory

research Convergent validity is assessed by the average variance extracted (AVE) for all items

associated with each construct The AVE value in the research ranged from 0786-0948 This

indicates that on average the construct explains over 50 of the variance of its items

For the composite reliability indexes (CRI) the values ranged from 0948 to 0989 which is

greater than 07 and is a desirable reliability for these latent variables (Bagozziand Yi 1988)

Furthermore the criterion demonstrated that all AVE values for the reflective constructs were

higher than the squared interconstruct correlations which indicates discriminate validity

(Fornell and Larcker 1981)The Cronbachs α ranged from 0838 to 0968 indicating the

internal consistency of the scale which is excellent The itemslsquo Cronbachs α index is

excellent at 0992 All of the data were analyzed by SPSS software that ran 5000

bootstrapping subsamples and the original sampleslsquo t-test values had a significant difference


17

at Plt 001 Similarly Table 6 shows the AVE values on the diagonal and squared

interconstruct correlations of the diagonal

Table 6 Correlation coefficients and discriminant validity

represents significant differences P lt 001

P lt 005Italics along the diagonal represent

the square root of AVE Correlation coefficients were calculated based on the average

correlation matrix of all original variables

Following the second-order measurement model related to the 4D-FLIPPED classroom

measurement scale the second-order variable was specified with all twenty indicators of the

ICA OCA FBK and TEC The total values of the AVE CRI and Cronbachs α for the item

variables were 0859 0967 and 0992 respectively After an analysis of all original data

factor loadings correlation coefficients and significance levels the results showed that the

indicators are acceptable and reliable

452 Structure model

As Sastedt et al (2019) suggested that if we use the standard repeated indicators approach to

identify the higher-order construct we would find that KNL and SKL explain nearly almost

entire variance of ITK and SAT (R2=1) To analyze the causal relationships in the predicted

model we conceptualized a reflective-reflective higher-order construct of studentslsquo BRM The

hypothesis of BRM and ITK are based on the lower-order components of ICA OCA FBK and

TEC The results in Table 7 show that the measure of KNL yield satisfactory levels of

convergent validity in terms of AVE (0948) and internal consistency reliability (CRI = 0989

Cronbachs α = 0917 reliability metric = 0925) similarly the measure of SKL exhibit

convergent validity (AVE = 0921) and other index reliability is shown in CRI = 0983

Cronbachs α = 0838 reliability metric = 0980

ICA OCA FBK TEC KNL SKL ITK SAT

ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18

The AVE of BRMis derived from loading 0611 for KNL and 0911 for SKL according to the

formula Similarly the Cronbachs α CRI and Reliability Metric index of BRM were manually

computed based on the lower-order component of KNL and SKL (Table 7) We found that all

indexes are satisfactorily valid and strongly support the previous hypothesis

Table 8 Discriminant validity assessment by using the HTMT criterion

KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005

Then we calculated the discriminant validity by using the HTMT criterion (Heterotrait Hetero

method Correlation Table 8) which is the mean value of the item correlations across

constructs The high-order constructslsquo HTMT are equal to the correlations between

lower-order components was generated by SPSS and manual computing) After analyzing the

structure model using bootstrapping with 5000 subsamples we found that all structural model

relationships are significant at Plt 001

Fig 9 shows that ICA OCA FBK and TEC are the main influencing factors of BRM and in

particular SKL has a strong effect on BRM (0911) In comparison KNL has a relatively weak

effect on BRM (0611) but is still larger than 05 which indicates the effectiveness is valid The

effect of BRM is strongly related to ITK (0755) The direct relationship between ITK and SAT

(0751) is stronger than the direct relationship between BRM and SAT (0259) The results

confirmed that the studentslsquo satisfaction is principally affected by ITK but not by BRM This

finding might be largely because BRM does not limit whether the generated ideas are useful or

Table 7 Reliability and validity statistics

Cronbachs α CRI AVE Reliability metric

KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19

practicable The R2 values of all the dependent latent variables for BRM ITK and SAT are

0830 0901 and 0786 respectively

Fig 9 Reflective-reflective stage two specification of the BRM and PLS-SEM results

Finally we calculated the cross-validated redundancy (Q2) for the high-order constructs of

BRM ITK and SAT which are 0567 0503 and 0666 respectively The Q2

values larger than

zero for a particular endogenous construct indicate that the path modellsquos predictive accuracy is

acceptable (Sarstedt et al 2014) Our data analysis confirms that all structural model

evaluation results are satisfactory (Table 9)

Table 9 Estimate results of the structure model

Control relationships SD coefficient β t

Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20

Model relationships Effects t

ICA rarr BRM 0252 13220

OCA rarr BRM 0254 8891

FBK rarrBRM 0249 19214

TEC rarrBRM 0255 9002

BRM rarrITK 0755 19588

BRM rarrSAT 0259 8586

ITK rarrSAT 0751 8586

Latent variable R2 Q2

BRM 0830 0567

ITK 0901 0503

SAT 0786 0666

represents significant differences at P lt 001

P lt 005

5 Discussion

General speaking young studentlsquos reject traditional teaching We tried different pedagogies in

classroom teaching and out-of-classroom activities This paper explored the entire processes of

the teaching curriculum activities of flipped classroom Six Thinking Hats innovative

performances and statistical analysis in the bilingual course of Insect Physiology and

Biochemistry

An increasing number of teachers are currently using a flipped classroom in higher education

The processes in our class include essential teaching procedures such as ICA OCA FBK and

TEC in different organizing styles The processes showed high student confidence motivation

and engagement lower cognitive loads (Turan and Goktas 2016) high degrees of student

satisfaction (Awidi and Parnter 2019) and other indirect educational outcomes such as

improving studentslsquo communication skills promoting more independent learners and


21

changing learning habits (Lo and Hew 2017 Akccedilayır et al 2018) Using a revised Blooms

digital knowledge dimension analysis we discussed some issues in professional insect science

questions and compared them with traditional teaching methods Surprisingly our data

suggested that Factual negative affects Metacognitive This finding can be either correct or

incorrect as one may underestimate or overestimate the actual level of competency relative to

the complexity of the task (Veenman et al 2006) The results also indicate that the

literature-based linking of insect science content knowledge to a flipped classroom about the

case enhances learning compared with traditional teaching The scores data strongly supported

a flipped classroom which is a valuable pedagogy in college education However the

statistical analysis revealed no significant differences at Plt 001 of the Creative item between

two groups in the student knowledge dimension Meanwhile one has to focus on teacherslsquo

workload to create materials feedback and studentslsquo engagement both in ICA and OCA in a

flipped teaching design In addition some researchers have observed that students in flipped

classrooms performed equally well on lower cognitive assignments but better on more

cognitively complex items (Morton and Colbert-Getz 2017)Flipped classroom education

indeed requires reduced time investment when preparing for the final exam but a comparison

of long-term measurements showed similar outcomes for students in traditional classrooms and

flipped classrooms (Bouwmeester et al 2019)

On the other hand the effectiveness of BRM has been widely debated when it proposes

principles and procedures of creative thinking It is believed that BRM is helpful in standard

idea generation and problem-solving methods in organization but the controversy has

continued for dozens of years In an experiment designed to answer the title question it was

concluded that group participation using BRM inhibits creative thinking (Donald et al 1958)

However the advantage vanishes for extremely complex problems (Kavadias and Sommer

2009) Interestingly FBK such as judgment or evaluation is closely related to group creative

performance Positive FBK promoted interpersonal interaction that benefited group creative

performance (Lu et al 2019) Our results suggested that essential teaching procedures

similarly affect the higher-order construction of BRM The path coefficients of ICA OCA

FBK and TEC are 0252 0254 0249 and 0255 respectively (Fig9)

―Six Thinking Hats is a deliberate process that exclusively shifts the thinkers attention to this

mode (Carl 1996) and involves more creative thinking the separate efficacy of each hat a

conceptual understanding of science and the quality of ideas and arguments (Goumlccedilmen and

Coşkun 2019Lin 2019) In our performance the thinking map and routine were implemented

to choose a specific biochemical insect experiment The scores that the students achieved

revealed that there are significant differences at Plt 001 between each hat After creative and

collative thinking the student groups achieved the target well We confirmed that the

participants under the yellow and green hats generated more quality ideas than the participants

under the red hat

If flipped classrooms and embedded techniques combined with BRM and ―Six Thinking Hats

the advantages of these pedagogies could be fully unleashed whereas traditional college


22

education required to earn a diploma is weak in creative thinking and may soon fall into disuse

The effective strategies described here lead students to dialogue with their teachers (Song et al

2019) and to freely express their views on every issue of the metacognitive processes such as

mentoring as role rehearsal and exposing students to authentic or situated problems and

examples The new model of a flipped classroom activates the studentslsquo vigorous challenging

performance and provides them with opportunities to engage in higher order thinking

processes (Falloon 2019)Furthermore cooperative learning improves studentslsquo

communication skills and enables them to build their teamwork and problem-solving skills

offline and online (Munir et al 2018Hernaacutendez-Selleacutes et al 2019)The different pedagogies

encourage the studentslsquo learning exchanging views regarding novel insect science and

discussing them in the classroom which greatly stimulates the studentslsquo creative and

innovative thinking and activates the learning atmosphere The results of the final exam of the

different groups in the three classes confirm the effects of our performances

6 Conclusions and findings

With more than thirteen years of exploration pedagogy improvement the bilingual course of

Insect Physiology and Biochemistry has importantly been brought into play in undergraduate

educationWe emphasize the basic professional vocabulary and make the students understand

the principals of insect science With the well-grounded essential major knowledge and

innovative thinking more than ten students have become winners of the national competition

in the last two years

Our SPSS analysis revealed that the metacognitive process of conceptual studies shows a

collinearity relationship but factually exhibits negative effectsBRM and ―Six Thinking Hats

in flipped classrooms generate higher quality and more innovative ideas than flipped

classrooms alone Furthermore the participants under yellow hats actively perform and stand

out above the others The PLS-SEM statistical analysis suggests that basic procedures of

teaching equally influence BRM and ITK SKL has a stronger effect on BRM than on KNL

which indicates that most BRM originate from technology performance BRM has a strong

effect on ITK and later strongly affects SAT In comparing BRM and ITK the students feel

satisfaction when they participate in an innovative thinking model We confirm that flipped

classroom embedded techniques combined with BRM and ―Six Thinking Hats improve the

studentslsquo enthusiasm for learning and participation and they more strongly enjoy the learning

process

References

1) Abeysekera L and Dawson P Motivation and cognitive load in the flipped classroom

Definition rationale and a call for research Journal of Higher Education Research and

Development 201534(1) 1ndash14 Doi101080072943602014934336


23

2) Achu DO and Ehizuelen MMO How teacher self-efficiency can be a driver for student

success Third 21st CAF Conference at Harvard in Boston USA September 2015 Vol

6 Nr 1

3) Anderson LW and Krathwohl DRA Taxonomy for Learning Teaching and Assessing

A Revision of Bloomlsquos Taxonomy of Educational Objectives Complete Edition Chap

8-13 2001 Longman New York

4) Awidi IT and Parnter MThe impact of a flipped classroom approach on student

learning experience Computers amp Education 2019 (128) 269ndash283Doi

101016jcompedu201809013

5) Bagozzi RP and Yi YOn the evaluation of structural equation models Journal of the

Academy of Marketing Science1988 16(1) 74ndash94

6) Barrows HS Taxonomy of problem-based learning methods Medical education1986

20(6) 481-486 Doi101111j1365-29231986tb01386x

7) Beebe RM De Costa Elena M The Santa Clara University Eastside Project

community service and the Spanish classroom Hispania 199376 884-891 Doi

102307343926

8) Betihavas V Bridgman H Kornhaber R Cross M The evidence for flipping outlsquo A

systematic review of the flipped classroom in nursing education Nurse Education

Today 2016 38 15ndash21 Doi 101016jnedt201512010

9) Bloom BS Engelhart MD Furst EJ Hill WH Krathwohl D R Taxonomy of

educational objectives The classification of educational goals Handbook I Cognitive

domain New York David McKay1956

10) Bouwmeester RAM de Kleijn RAM van den Berg IET ten Cate OTJ van Rijen HVM

Westerveld HE Flipping the medical classroom Effect on workload interactivity

motivation and retention of knowledge Computers amp Education 2019 (139) 118ndash128

Doi 101016jcompedu201905002

11) Bridgham R Heuristic science teaching In A Symposium on Heuristic TeachingEd

by Richard E S Stanford Center for Research and Development in Teaching 1970

32-42

12) Carl WJ III Six Thinking Hats Argumentativeness and response to thinking model

Annual Meeting of the Southern States Communication Association (Memphis TN

March 27-31) 1996 P42

13) Crouch H and Mazur E Peer instruction Ten years of experience and results American

Journal of Physics 2001 69(9) 970ndash977 Doi10111911374249

14) De Bono E Six thinking hats Cambridge Little Brown and Company 1956

15) De Bono E Serious creativity The Journal for Quality and Participation 199518

12-18


24

16) Deslauriers L Schelew E and Wieman C Improved learning in a large-enrollment

physics class Science (New York NY)2011 332 (6031)

862-864Doi101126science1201783

17) Donald W T Paul CB Clifford H B Does group participation when using

brainstorming facilitate or inhibit active thinking Administrative Science Quarterly

1958 3(1)23-47Doi 1023072390603

18) Driscoll M Blended Learning Letlsquos Get beyond the Hype IBM Global Services2002

httpwww-07ibmcomservicespdfblended_learning

19) Echevarria J Short DJThe SIOP Model A professional development framework for a

comprehensive school-wide intervention Center for Research on the Educational

Achievement and Teaching of English Language Learners 2011Doi

10131402125738886

20) Fornell C and Larcker DF Evaluating structural equation models with unobservable

variables and measurement error Journal of Marketing Research 198118 39-50

Doi1023073151312

21) Goumlkccedile A Murat A The flipped classroom A review of its advantages and challenges

Computers amp Education 2018 (126) 334ndash345 Doi 101016jcompedu201807021

22) Goumlccedilmen Ouml Coşkunb H The effects of the six thinking hats and speed on creativity in

brainstormingThinking Skills and Creativity 2019 (31) 284ndash295

Doi101016jtsc201902006

23) Hans H Dorina G If PBL Is the answer then what Is the problem Journal of Problem

Based Learning in Higher Education 20175(2)1-21

Doi105278ojsjpblhev5i21491

24) Henry S McInnes BT Literature Based Discovery Models methods and trends

Journal of Biomedical Informatics 2017 (74) 20ndash32 Doi 101016jjbi201708011

25) Jagla VM and Tice KC Educating teachers and tomorrows students through

service-learning pedagogyIn Advances in Service-Learning Research Ed by

TinklerA S Information Age Publishing Inc 2019

26) Kavadias S Sommer SC The effects of problem structure and team diversity on

brainstorming effectivenessINFORMS 2009 Doi101287mnsc10901079

27) Khine M S Lourdusamy A Blended learning approach in teacher education

combining face-to-face instruction multimedia viewing and online discussion British

Journal of Educational Technology 2003 34(5)671ndash675 Doi

101046j0007-1013200300360x

28) Lee YJ Kim MJ Jin QN Yoon HG Matsubara KJ Revised bloomlsquos taxonomymdashthe

Swiss Army Knife in curriculum research in East-Asian Primary Science Curricula

An Overview Using Revised Bloomlsquos Taxonomy Springer Briefs in EducationDoi

101007978-981-10-2690-4_2


25

29) Li JunOn Structural Model of Knowledge Points in View of Intelligent Teaching In

Frontier and Future Development of Information Technology in Medicine and

Education Edby S Li et al Lecture Notes in Electrical Engineering 269 Doi

101007978-94-007-7618-0_383

30) Likert RA Technique for the measurement of attitudes Archives of Psychology

1932140 1-55 Doi 2731047

31) Lin Yu-Ren Student positions and web-based argumentation with the support of the six

thinking hatsComputers amp Education2019 139 191-206

Doi101016jcompedu201905013

32) Liu XM A longitudinal study of dynamic changes in and contributing factors of learner

belief of Chinese foreign language learners English Language Teaching 2018 11(7)

61-70 Doi 105539eltv11n7p61

33) Lo Chung Kwan and Hew KheFoon A critical review of flipped classroom challenges

in K-12 education possible solutions and recommendations for future research

Research and Practice in Technology Enhanced Learning 2017 (12)4 Doi

101186s41039-016-0044-2

34) Lu Kelong QiaoXinuo HaoNing Praising or keeping silent on partnerlsquos ideas

Leading brainstorming in particular ways Neuropsychologia 2019 (124) 19ndash30 Doi

101016 j neuropsychologia201901004

35) Mazur E Peer Instruction A Users Manual New Jersey Prentice Hall Series in

Educational Innovation 1997

36) Menon D and Sadler TD Sources of science teaching self-efficacy for preservice

elementary teachers in science content courses International Journal of Science and

Mathematics Education 2018 16(5)p835-855 Doi101007s10763-017-9813-7

37) Morton DA and Colbert-Getz JMMeasuring the impact of the flipped anatomy

classroom The importance of categorizing an assessment by Blooms

taxonomyAnatomical Sciences Education 2017 (10)170-175 Doi101002ase1635

38) Murillo-Zamorano LR Loacutepez Saacutenchez JoseacuteAacute amp Godoy-Caballero AL How the

flipped classroom affects knowledge skills and engagement in higher education

Effects on students satisfaction Computers amp Education2019 21 (in press)


39) Nematollahi B Behjat F Kargar A A A meta-analysis of vocabulary learning

strategies of EFL learnersEnglish Language Teaching 2017 10 (5)1-10 Doi

105539eltv10n5p1

40) Nijstad BA De Dreu CKW Rietzschel EF Baas M The dual pathway to creativity

model Creative ideation as a function of flexibility and persistence European Review

of Social Psychology 2010 21(1) 34-77 Doi10108010463281003765323


26

41) OrhanE and Kadir B Effect of web assisted education supported by Six Thinking Hats

on students academic achievement in science and technology classes European

Journal of Educational Research 2014 3(1)9-23 Doi 1012973eu-jer319

42) Osborn A F Applied imagination Principles and procedures of creative problem

solving New York NY Charles Scribnerlsquos Sons 1953(3)107

43) Oumlznur G Hamit C The effects of the six thinking hats and speed on creativity in

brainstormingThinking Skills and Creativity2019

31284-295 Doi101016jtsc201902006

44) Reidsema C Hadgraft R and Kavanagh L Introduction to the Flipped Classroom In

The Flipped ClassroomPractice and Practices in Higher Education Edited by

Reidsema C Kavanagh L Hadgraft R Smith N Springer Nature Singapore Pte Ltd

2017 3-14Doi 101007978-981-10-3413-8

45) Rossiter J R Lilien G L New Brainstorming Principles Australian Journal of

Management 1994 19(1)61-72 Doi101177031289629401900104

46) Sarstedt M Ringle C M Smith D Reams R Hair JF Partial least squares structural

equation modeling (PLS-SEM) useful tool for family business researchers Journal of

Family Business Strategy 2014 (5) 105ndash115 Doi101016jjfbs201401002

47) Sarstedt M Hair JF Cheah JH Becker JM Ringle CM How to specify estimate and

validate higher-order constructs in PLS-SEM Australasian Marketing Journal

Doiorg101016jausmj 2019 05003

48) Schleicher A Student AchievementIn Encyclopedia of Quality of Life and Well-Being

Research Edby Michalos AC 20146403-6411 Doi 101007978-94-007-0753-5

49) Swacha KY Service-learning in the second language writing classroom Future

research directions TESOL Journal 20178(3) 2-21 Doi101002tesj321

50) Toulmin SE The Uses of ArgumentCambridge UK Cambridge University Press

2003

51) Turan Z Goktas Y The Flipped Classroom instructional efficency and impact of

achievement and cognitive load levels Journal of e-Learning and Knowledge Society

2016 12(4)51-62

52) VerspoorA Wu K B Textbooks and educational development Health Services

Manpower Review 2010 8(4)20-3 Doi

1013063D932B5A-16B1-11D7-8645000102C1865D

53) Winarno S Muthu KS Ling LS Direct problem-based Learning (DPBL) a framework

for integrating direct instruction and problem-based learning approach International

Education Studies 2018 11(1) 119-126 Doi105539iesv11n1p119


2

of undergraduate and postgraduate students Bilingual teaching promotes reform in education

and its system for economic globalization reflects a higher quality of education and updated

awareness of innovation improves teaching practices accelerates teaching methodologies

implements teaching measures and maximizes teaching achievements Furthermore bilingual

teaching optimizes the knowledge structure of personnel and drives education toward a more

elevated hierarchy

This paper focuses on the popularized flipped classroom BRM and ―Six Thinking Hats aims

to explore the effects of embedded techniques of teaching and estimates the quality of different

pedagogies in academic education (Fig1)

Fig 1 An illustration of the executable training ideas of the course Insect Physiology and Biochemistry

2 Theoretic Background

The pedagogies of teachers applied in the classroom leads to the process of teaching described

as ―pedagogies are dependent on teacherlsquos personalities and preferences Some investigators

focused on beliefs and suggested that the beliefs of self-efficiency of both teachers and students

can assist learners in improving their language learning (Achu and Ehizuelen 2015 Liu 2018

Menon and Sadler 2018) However increasing numbers of educational specialists suggest that

students should take charge of the learning process and teachers act just as learning services

(Swacha 2017 Jagla and Tice 2019) This view is the concept of a ―flipped classroom

(Reidsema 2017) and most educators consider this to be a type of blended learning

(Abeysekera and Dawson 2015) The characteristics of blended learning combine or mix


3





































2009)





4





3 Methods

















the pedagogies

















5










































6

















1

FPM 1

Evidence FPCM






1

FPCM 1

Backings

FPCM



substances

1

FPCM 1

Rebuttals

FPC




1

FPC 1


7



Conceptual





















34 BRM experiment




model













8





















Facts figures

and information



Emotionsfeelings

hunches intuition



Cautiontruth

judgment critical






experiment

Advantages benefits

savings








9


creativity and new

ideas























119860119881119864 = 120582119894119899119894=1


( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+( (120579119894 )119899

119894=1 )

(Bagozzi and Yi 1988) or 119862119877119868 =( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+119899minus (120582119894 )119899

119894=12 (Biemer et al 2009)













10


4 Results




















11






12



exam


13


final exam


Paired Differences














zero







14























Items

Mean SD t P


Remember 29950 22025 7846 6699 7635 6575 0005 0007

Understand 33925 25650 1986 2009 34171 25533 0000 0000

Apply 2325 4375 0854 4826 5446 1813 0012 167

Analyze 26025 19250 7556 5251 6888 7331 0006 0005

Evaluate 31650 24700 5690 4243 11125 11644 0002 0001

Create 0625 0375 1250 0750 1000 1000 391 391

Note


Plt 005


15

43 BRM experiment






Mean SD t df P

Original 0000 0000a

Flexible 119333 13317 15521 2 0004

Persistence 70000 6928 17500 2 0003

Quality 36000 6928 9000 2 0012
























16


























17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





3





































2009)





4





3 Methods

















the pedagogies

















5










































6

















1

FPM 1

Evidence FPCM






1

FPCM 1

Backings

FPCM



substances

1

FPCM 1

Rebuttals

FPC




1

FPC 1


7



Conceptual





















34 BRM experiment




model













8





















Facts figures

and information



Emotionsfeelings

hunches intuition



Cautiontruth

judgment critical






experiment

Advantages benefits

savings








9


creativity and new

ideas























119860119881119864 = 120582119894119899119894=1


( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+( (120579119894 )119899

119894=1 )

(Bagozzi and Yi 1988) or 119862119877119868 =( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+119899minus (120582119894 )119899

119894=12 (Biemer et al 2009)













10


4 Results




















11






12



exam


13


final exam


Paired Differences














zero







14























Items

Mean SD t P


Remember 29950 22025 7846 6699 7635 6575 0005 0007

Understand 33925 25650 1986 2009 34171 25533 0000 0000

Apply 2325 4375 0854 4826 5446 1813 0012 167

Analyze 26025 19250 7556 5251 6888 7331 0006 0005

Evaluate 31650 24700 5690 4243 11125 11644 0002 0001

Create 0625 0375 1250 0750 1000 1000 391 391

Note


Plt 005


15

43 BRM experiment






Mean SD t df P

Original 0000 0000a

Flexible 119333 13317 15521 2 0004

Persistence 70000 6928 17500 2 0003

Quality 36000 6928 9000 2 0012
























16


























17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





4





3 Methods

















the pedagogies

















5










































6

















1

FPM 1

Evidence FPCM






1

FPCM 1

Backings

FPCM



substances

1

FPCM 1

Rebuttals

FPC




1

FPC 1


7



Conceptual





















34 BRM experiment




model













8





















Facts figures

and information



Emotionsfeelings

hunches intuition



Cautiontruth

judgment critical






experiment

Advantages benefits

savings








9


creativity and new

ideas























119860119881119864 = 120582119894119899119894=1


( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+( (120579119894 )119899

119894=1 )

(Bagozzi and Yi 1988) or 119862119877119868 =( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+119899minus (120582119894 )119899

119894=12 (Biemer et al 2009)













10


4 Results




















11






12



exam


13


final exam


Paired Differences














zero







14























Items

Mean SD t P


Remember 29950 22025 7846 6699 7635 6575 0005 0007

Understand 33925 25650 1986 2009 34171 25533 0000 0000

Apply 2325 4375 0854 4826 5446 1813 0012 167

Analyze 26025 19250 7556 5251 6888 7331 0006 0005

Evaluate 31650 24700 5690 4243 11125 11644 0002 0001

Create 0625 0375 1250 0750 1000 1000 391 391

Note


Plt 005


15

43 BRM experiment






Mean SD t df P

Original 0000 0000a

Flexible 119333 13317 15521 2 0004

Persistence 70000 6928 17500 2 0003

Quality 36000 6928 9000 2 0012
























16


























17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





5










































6

















1

FPM 1

Evidence FPCM






1

FPCM 1

Backings

FPCM



substances

1

FPCM 1

Rebuttals

FPC




1

FPC 1


7



Conceptual





















34 BRM experiment




model













8





















Facts figures

and information



Emotionsfeelings

hunches intuition



Cautiontruth

judgment critical






experiment

Advantages benefits

savings








9


creativity and new

ideas























119860119881119864 = 120582119894119899119894=1


( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+( (120579119894 )119899

119894=1 )

(Bagozzi and Yi 1988) or 119862119877119868 =( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+119899minus (120582119894 )119899

119894=12 (Biemer et al 2009)













10


4 Results




















11






12



exam


13


final exam


Paired Differences














zero







14























Items

Mean SD t P


Remember 29950 22025 7846 6699 7635 6575 0005 0007

Understand 33925 25650 1986 2009 34171 25533 0000 0000

Apply 2325 4375 0854 4826 5446 1813 0012 167

Analyze 26025 19250 7556 5251 6888 7331 0006 0005

Evaluate 31650 24700 5690 4243 11125 11644 0002 0001

Create 0625 0375 1250 0750 1000 1000 391 391

Note


Plt 005


15

43 BRM experiment






Mean SD t df P

Original 0000 0000a

Flexible 119333 13317 15521 2 0004

Persistence 70000 6928 17500 2 0003

Quality 36000 6928 9000 2 0012
























16


























17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





6

















1

FPM 1

Evidence FPCM






1

FPCM 1

Backings

FPCM



substances

1

FPCM 1

Rebuttals

FPC




1

FPC 1


7



Conceptual





















34 BRM experiment




model













8





















Facts figures

and information



Emotionsfeelings

hunches intuition



Cautiontruth

judgment critical






experiment

Advantages benefits

savings








9


creativity and new

ideas























119860119881119864 = 120582119894119899119894=1


( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+( (120579119894 )119899

119894=1 )

(Bagozzi and Yi 1988) or 119862119877119868 =( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+119899minus (120582119894 )119899

119894=12 (Biemer et al 2009)













10


4 Results




















11






12



exam


13


final exam


Paired Differences














zero







14























Items

Mean SD t P


Remember 29950 22025 7846 6699 7635 6575 0005 0007

Understand 33925 25650 1986 2009 34171 25533 0000 0000

Apply 2325 4375 0854 4826 5446 1813 0012 167

Analyze 26025 19250 7556 5251 6888 7331 0006 0005

Evaluate 31650 24700 5690 4243 11125 11644 0002 0001

Create 0625 0375 1250 0750 1000 1000 391 391

Note


Plt 005


15

43 BRM experiment






Mean SD t df P

Original 0000 0000a

Flexible 119333 13317 15521 2 0004

Persistence 70000 6928 17500 2 0003

Quality 36000 6928 9000 2 0012
























16


























17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





7



Conceptual





















34 BRM experiment




model













8





















Facts figures

and information



Emotionsfeelings

hunches intuition



Cautiontruth

judgment critical






experiment

Advantages benefits

savings








9


creativity and new

ideas























119860119881119864 = 120582119894119899119894=1


( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+( (120579119894 )119899

119894=1 )

(Bagozzi and Yi 1988) or 119862119877119868 =( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+119899minus (120582119894 )119899

119894=12 (Biemer et al 2009)













10


4 Results




















11






12



exam


13


final exam


Paired Differences














zero







14























Items

Mean SD t P


Remember 29950 22025 7846 6699 7635 6575 0005 0007

Understand 33925 25650 1986 2009 34171 25533 0000 0000

Apply 2325 4375 0854 4826 5446 1813 0012 167

Analyze 26025 19250 7556 5251 6888 7331 0006 0005

Evaluate 31650 24700 5690 4243 11125 11644 0002 0001

Create 0625 0375 1250 0750 1000 1000 391 391

Note


Plt 005


15

43 BRM experiment






Mean SD t df P

Original 0000 0000a

Flexible 119333 13317 15521 2 0004

Persistence 70000 6928 17500 2 0003

Quality 36000 6928 9000 2 0012
























16


























17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





8





















Facts figures

and information



Emotionsfeelings

hunches intuition



Cautiontruth

judgment critical






experiment

Advantages benefits

savings








9


creativity and new

ideas























119860119881119864 = 120582119894119899119894=1


( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+( (120579119894 )119899

119894=1 )

(Bagozzi and Yi 1988) or 119862119877119868 =( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+119899minus (120582119894 )119899

119894=12 (Biemer et al 2009)













10


4 Results




















11






12



exam


13


final exam


Paired Differences














zero







14























Items

Mean SD t P


Remember 29950 22025 7846 6699 7635 6575 0005 0007

Understand 33925 25650 1986 2009 34171 25533 0000 0000

Apply 2325 4375 0854 4826 5446 1813 0012 167

Analyze 26025 19250 7556 5251 6888 7331 0006 0005

Evaluate 31650 24700 5690 4243 11125 11644 0002 0001

Create 0625 0375 1250 0750 1000 1000 391 391

Note


Plt 005


15

43 BRM experiment






Mean SD t df P

Original 0000 0000a

Flexible 119333 13317 15521 2 0004

Persistence 70000 6928 17500 2 0003

Quality 36000 6928 9000 2 0012
























16


























17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





9


creativity and new

ideas























119860119881119864 = 120582119894119899119894=1


( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+( (120579119894 )119899

119894=1 )

(Bagozzi and Yi 1988) or 119862119877119868 =( 120582119894 )119899119894=1

2

( 120582119894 )119899119894=1

2+119899minus (120582119894 )119899

119894=12 (Biemer et al 2009)













10


4 Results




















11






12



exam


13


final exam


Paired Differences














zero







14























Items

Mean SD t P


Remember 29950 22025 7846 6699 7635 6575 0005 0007

Understand 33925 25650 1986 2009 34171 25533 0000 0000

Apply 2325 4375 0854 4826 5446 1813 0012 167

Analyze 26025 19250 7556 5251 6888 7331 0006 0005

Evaluate 31650 24700 5690 4243 11125 11644 0002 0001

Create 0625 0375 1250 0750 1000 1000 391 391

Note


Plt 005


15

43 BRM experiment






Mean SD t df P

Original 0000 0000a

Flexible 119333 13317 15521 2 0004

Persistence 70000 6928 17500 2 0003

Quality 36000 6928 9000 2 0012
























16


























17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





10


4 Results




















11






12



exam


13


final exam


Paired Differences














zero







14























Items

Mean SD t P


Remember 29950 22025 7846 6699 7635 6575 0005 0007

Understand 33925 25650 1986 2009 34171 25533 0000 0000

Apply 2325 4375 0854 4826 5446 1813 0012 167

Analyze 26025 19250 7556 5251 6888 7331 0006 0005

Evaluate 31650 24700 5690 4243 11125 11644 0002 0001

Create 0625 0375 1250 0750 1000 1000 391 391

Note


Plt 005


15

43 BRM experiment






Mean SD t df P

Original 0000 0000a

Flexible 119333 13317 15521 2 0004

Persistence 70000 6928 17500 2 0003

Quality 36000 6928 9000 2 0012
























16


























17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





11






12



exam


13


final exam


Paired Differences














zero







14























Items

Mean SD t P


Remember 29950 22025 7846 6699 7635 6575 0005 0007

Understand 33925 25650 1986 2009 34171 25533 0000 0000

Apply 2325 4375 0854 4826 5446 1813 0012 167

Analyze 26025 19250 7556 5251 6888 7331 0006 0005

Evaluate 31650 24700 5690 4243 11125 11644 0002 0001

Create 0625 0375 1250 0750 1000 1000 391 391

Note


Plt 005


15

43 BRM experiment






Mean SD t df P

Original 0000 0000a

Flexible 119333 13317 15521 2 0004

Persistence 70000 6928 17500 2 0003

Quality 36000 6928 9000 2 0012
























16


























17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





12



exam


13


final exam


Paired Differences














zero







14























Items

Mean SD t P


Remember 29950 22025 7846 6699 7635 6575 0005 0007

Understand 33925 25650 1986 2009 34171 25533 0000 0000

Apply 2325 4375 0854 4826 5446 1813 0012 167

Analyze 26025 19250 7556 5251 6888 7331 0006 0005

Evaluate 31650 24700 5690 4243 11125 11644 0002 0001

Create 0625 0375 1250 0750 1000 1000 391 391

Note


Plt 005


15

43 BRM experiment






Mean SD t df P

Original 0000 0000a

Flexible 119333 13317 15521 2 0004

Persistence 70000 6928 17500 2 0003

Quality 36000 6928 9000 2 0012
























16


























17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





13


final exam


Paired Differences














zero







14























Items

Mean SD t P


Remember 29950 22025 7846 6699 7635 6575 0005 0007

Understand 33925 25650 1986 2009 34171 25533 0000 0000

Apply 2325 4375 0854 4826 5446 1813 0012 167

Analyze 26025 19250 7556 5251 6888 7331 0006 0005

Evaluate 31650 24700 5690 4243 11125 11644 0002 0001

Create 0625 0375 1250 0750 1000 1000 391 391

Note


Plt 005


15

43 BRM experiment






Mean SD t df P

Original 0000 0000a

Flexible 119333 13317 15521 2 0004

Persistence 70000 6928 17500 2 0003

Quality 36000 6928 9000 2 0012
























16


























17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





14























Items

Mean SD t P


Remember 29950 22025 7846 6699 7635 6575 0005 0007

Understand 33925 25650 1986 2009 34171 25533 0000 0000

Apply 2325 4375 0854 4826 5446 1813 0012 167

Analyze 26025 19250 7556 5251 6888 7331 0006 0005

Evaluate 31650 24700 5690 4243 11125 11644 0002 0001

Create 0625 0375 1250 0750 1000 1000 391 391

Note


Plt 005


15

43 BRM experiment






Mean SD t df P

Original 0000 0000a

Flexible 119333 13317 15521 2 0004

Persistence 70000 6928 17500 2 0003

Quality 36000 6928 9000 2 0012
























16


























17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





15

43 BRM experiment






Mean SD t df P

Original 0000 0000a

Flexible 119333 13317 15521 2 0004

Persistence 70000 6928 17500 2 0003

Quality 36000 6928 9000 2 0012
























16


























17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





16


























17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





17














452 Structure model












ICA 0897

OCA 0809 0887

FBK 0826 0826 0941

TEC 0844 0820 0843 0908

KNL 0850 0861 0924 0874 0974

SKL 0878 0852 0889 0875 0906 0960

ITK 0795 0784 0851 0805 0879 0864 0903

SAT 0800 0791 0895 0817 0928 0880 0867 0940


18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





18






KNL SKL ITK BRM SAT

KNL

SKL 0879

ITK 0928 0867

BRM - 0805 0972

SAT 0906 0864 0880 -


P lt 005
















KNL 0917 0989 0948 0925

SKL 0838 0983 0921 0980

ITK 0968 0957 0816 0972

BRM 0864 0744 0602 0761


19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





19






values larger than






Average rarr

KNL 970 8862

SKL 989 15257

ITK 997 28901

SAT 949 6740


20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





20










BRM 0830 0567

ITK 0901 0503

SAT 0786 0666


P lt 005

5 Discussion





Biochemistry








21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





21






































under the red hat




22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





22
































process

References





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





23



6 Nr 1






101016jcompedu201809013




20(6) 481-486 Doi101111j1365-29231986tb01386x



102307343926













32-42



March 27-31) 1996 P42





12-18


24



862-864Doi101126science1201783



1958 3(1)23-47Doi 1023072390603






10131402125738886



Doi1023073151312





Doi101016jtsc201902006














101046j0007-1013200300360x




101007978-981-10-2690-4_2


25




101007978-94-007-7618-0_383


1932140 1-55 Doi 2731047






61-70 Doi 105539eltv11n7p61




101186s41039-016-0044-2


















105539eltv10n5p1





26








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2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





25




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1932140 1-55 Doi 2731047






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26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D





26








31284-295 Doi101016jtsc201902006




2017 3-14Doi 101007978-981-10-3413-8


Management 1994 19(1)61-72 Doi101177031289629401900104












2003



2016 12(4)51-62



1013063D932B5A-16B1-11D7-8645000102C1865D




Documents

Bilingual Teaching Pedagogies in Academic Practice: Embed