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Aug. 18-20, 2016Kyoto, Japan
Kyoto University of Foreign Studies
KEYNOTE ABSTRACT
The Learner-Centered Paradigm of Education and Training
Charles M. Reigeluth Indiana University
This presentation addresses how to help people learn for both practitioners and researchers. It is based on Chapter 1 in the new Volume IV of Instructional-Design Theories and Models, which is subtitled “The Learner-Centered Paradigm of Education.” Based on Elaboration Theory, Chapter 1 is an “epitome” of the book that provides a conceptual framework and high-level set of principles for the learner-centered paradigm.
The presentation begins with a clarification of what the learner-centered paradigm is and how it is different from the teacher-centered paradigm that was developed during the Industrial Age. It describes how time-based student progress forces slower learners to move on before they have mastered the current material, making it more difficult for them to learn related material in the future and thereby virtually condemning them to flunk out. Time-based student progress also holds faster learners back, which discourages them and squanders talent that our communities desperately need. This paradigm made sense in the Industrial Age when manual labor was the most common form of work and consequently we did not need to educate many people to high levels – in fact, we needed a system that would separate out the laborers from the managers and professional people. The educational system was designed to leave many children behind.
But now in the digital age, knowledge work is becoming the predominant form of work, and we therefore need to educate far more people to far higher levels. Therefore, instead of holding time constant, which forces achievement to vary, we must hold achievement constant at a mastery level and allow each student the amount of time needed to reach mastery. This fundamental change from time-based to learning-based student progress requires fundamental changes throughout the rest of an educational system. It requires changes from standardized to personalized learning (from teacher lesson plans to personal learning plans), from norm-referenced to criterion-referenced student assessment, from graded report cards to records of competencies for each student, from subject-based to task-based instruction (project-based, problem-based, inquiry-based, and maker-based) with just-in-time tutorials, and from individual/competitive to collaborative learning. It requires changes in the teacher’s role from sage on the stage to guide on the side, changes in the student’s role from passive, teacher-directed to active, self-directed, and changes in technology’s role from a tool primarily for teachers to one primarily for students. This means grade levels are replaced by continuous progress, courses are replaced by projects (and other kinds of tasks), classrooms are replaced by learning studios, and testing is fully integrated into instruction (as in the Khan Academy), rather than being a separate, end-of course event.
These are not piecemeal changes. They are fundamental changes in the paradigm of education and training, much like the change from the railroad to the automobile as a paradigm of
transportation. Such fundamental change is required because of the personal need for learning-based rather than time-based student progress and because of the societal need to no longer sort out laborers from managers to the extent we have in the past.
Next, this presentation identifies some early pioneers of the learner-centered paradigm of education: John Dewey, Maria Montessori, John Carroll, and Benjamin Bloom. And it describes the theoretical foundations of this paradigm: cognitivism’s Information Processing Theory, Schema Theory, and Mental Models; constructivism (e.g., Piaget and Vygotsky), and humanism (Carl Rogers).
Most importantly, the presentation now describes what the learner-centered paradigm is like, beginning with the values that guide it. Values about ends (learning goals) include:
Development of intrinsic motivation and love of learning.Development of learner self-regulation skills (how to learn).Mastery of knowledge and skills, including transfer to varied and real-world contexts.Development of collaboration skills.Emotional, social, and character development, including empathy and desire tocontribute to one’s community.
Values about means (instruction) include:The pace of instruction should be customized to each learner (attainment-based learnerprogress).The content of instruction should be customized to each learner (individual needs,interests, talents, and goals).The methods of instruction should be customized to each learner (individual learningpreferences).The methods of assessment should be customized to each learner (individual needs,interests, talents, and goals).Intrinsic motivation and love of learning should be cultivated.Learners should typically learn by doing (task-centered instruction).Learners should receive just-in-time support while learning by doing (instructionalscaffolding).Learners should learn much from peers through collaboration.Learners should be taught to set their own goals and manage their own instruction asmuch as possible (self-determination, self-regulated learning).Learners should be involved in assessing their own learning (self-reflection, self-evaluation).Both formative and summative assessment should occur throughout instruction(continuous, integrated assessment).
Finally, universal principles for the learner-centered paradigm are described. The first principle is attainment-based instruction, which includes:
1.1 Attainment-based learner progress 1.2 Attainment-based learner assessment
1.3 Attainment-based learner records The second principle is task-centered instruction, which includes:
2.1 Task environment (project-, problem-, inquiry-, and maker-based) 2.2 Scaffolding (adjusting, coaching, and instructing)
The third principle is personalized instruction, which includes: 3.1 Personalized goals (long-term and short-term) 3.2 Personalized task environment (task selection, collaboration, and self-regulation) 3.3 Personalized scaffolding (quantity and quality) 3.4 Personalized assessment (personalized assessor and representation) 3.5 Personalized reflection (on the learning process and learning outcome)
Fourth is changed roles, which include: 4.1 Teacher roles (to assist learners in setting goals, designing or selecting tasks,
facilitating task performance, facilitating learning, evaluating performance and learning, and mentoring the learner)
4.2 Learner roles (active learner, self-regulated learner, learner as teacher) 4.3 Technology roles (recordkeeping for learning, planning for learning, instruction for
learning, and assessment for and of learning) The final major principle is changed curriculum, which includes:
5.1 Expanded curriculum 5.2 Fundamentally restructured curriculum
The effects of using game in cooperative learning strategy on learning outcome of students with different learning motivations
Eva Handriyantini [email protected]
Lecturer STIKI Malang
Malang, Indonesia
I Wayan Ardhana [email protected]
Professor Universitas Negeri Malang
Malang, Indonesia
Punadji Setyosari [email protected]
Professor Universitas Negeri Malang
Malang, Indonesia
I Nyoman Sudana Degeng [email protected]
Professor Universitas Negeri Malang
Malang, Indonesia
Abstract. The game in learning can be used to increase the learning motivation of students, and having a contribution to development of students learning outcome. Research design used in this research is factorial non-equivalent control group design, where the research subject is students at 4th grade at SDN Lowokwaru III, Malang. Moderator variables in this research are learning motivations, grouped into high learning motivation and low learning motivation. Data analysis technique used in this research is ANCOVA ( Analysis of Covariance ) rank two 2x2. The instruments used in the learning motivation in this research adopting from Motivated Strategies for Learning Questionnaire (MSLQ) (Pintrich et. al., 1990). A scale of measurement a motivation in MSLQ contains 3 a major component indicators: (1) Intrinsic Goal Orientation; (2) Extrinsic Goal Orientation; (3) Task Value; (4) Control Beliefs; (5) Self-Efficacy; (6) Test anxiety. Based on data analysis, research outcome can be summarized as follows: (1) there is difference between average learning result of student group which use game-assisted cooperative learning strategy and average learning result of student group which use cooperative learning strategy without game; (2) there is difference between average learning result of students who have low learning motivation and average learning result of students who have high learning motivation at all treatment groups; (3) there is significant difference of average learning result based on interaction between treatment group with game-assisted cooperative learning strategy and treatment group with non-game-assisted cooperative learning strategy, and learning motivation (low and high).
Key words: Game, Motivation, Learning Outcomes, cooperative learning strategy
INTRODUCTION
Advances in information and communication technology bring great impact to many aspects of life,
including in education and learning. In learning process, computer has been integrated as a learning tool.
Nowadays, computer-assisted learning media has developed in almost all fields of learning. Computer has
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a role as assisting and supporting media in learning process or it is commonly known as Computer-
Assisted Instruction (CAI).
Generally speaking, game can be grouped into 3 categories, i.e. educational games, leisure games,
educational leisure games (Ulicsak, 2009). Educational games, or some literature refers to it as
instructional games, are designed with learning materials to support instruction and learning process
explicitly (Kebritchi, 2010). There are 3 important aspects in a learning game, i.e.: 1) Motivation:
motivation and participation have formed long time results by using game in class instruction (Joyce et al.,
2009); 2) skill development: according to McFarlane, et al.(2002) this includes for example: strategic
thinking, planning, communication, application number, negotiation skills, group decision making, data
control and immersive learning environment; 3) Learning environment: digital game can create 'semiotic
domain', which is a group of practices having more than one skill, (such as verbal and written language,
picture, equation, symbol, sound, graphics, artefacts,etc.) to coomunicate with other type’ (Gee, 2003).
Kebritchi & Hirumi (2008) claimed that learning strategy using game will be more effective, if it is used
in field of study which is considered to be difficult or complicated. That is because game has several
advantages such as: there is facility for interactive action instead of merely explanation, creating
motivation and comfort, it can be used at different learning model in learning process, it can help to
amplify student's learning result, and it can support interactive activity and problem solving context.
According to Bright (1985), educational game can be used not only for teaching basic operation skill at
mathematics learning, but it will also improve student's cognitive ability.
Slavin (2010) explained that in cooperative learning strategy with Student Teams
Achievement Division (STAD) model, students are placed in a study group consisting of four to five
students who have different ability or different gender, races, ethnic groups, or other social groups.
According to Slavin, STAD can work well, if the subject of study is single, has exact answer, and it may
be used in mathematical learning, reading, language and mechanics (Robinson et al., 2008).
Motivation is internal process which activates, guides and keeps behavior from time to time
(Slavin, 2010). Motivaion to learn directs student's behavir to achieve. There are 6 factors that influence
motivation in learning process, i.e: (1) dreams or aspiration of the learner, (2) ability to learn, (3)
student's physical and psychological condition, (4) environmental condition, either physically and
socially, (5) dynamical elements of learning, such as study materials, learning aid tool, learning
atmosphere, etc. (6) teacher's effort to teach according to student's needs (Ali Imron, 1996).
RESEARCH DESIGN & METHODS
This research is a quantitative research with quasi-experimental approach. Independent variable in this
research is game users in cooperative learning. The dependent variable is learning outcome. Materials to
be taught in this experiment are mathematics subject for 4th grader which consist: (1) angle; (2) largest
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common divisor; (3) integers.
The subject in this research is 4th grade primary school students at SDN Lowokwaru 3 Malang, with
total of 2 classes, and each class consists of around 30-48 students. Based on this research subject from 2
classes, we design: each student per class will follow tests to measure their initial knowledge. Students
who have high/low initial knowledge are then grouped randomly into student groups consisting of 4-6
students per group. Then we choose such that class 4A will get treatment to use game for cooperative
learning. In the mean time, class 4B will get treatment to not use game for cooperative learning.
The number of encounter for this treatment is designed to be 10 times. In practical level, the treatment
using game assisted cooperative learning in class 4A, is done by providing each group with 1 laptop/PC
which each has mathematic-learning game application pre-installed. Cooperative learning is done at 10
face-to-face meetings, with duration of 2 learning hours (90 minutes) per meeting.
The research instrument that we used is evaluation of mathematical learning results and learning
motivation. The instrument for learning motivation to be used here is adopted from Motivated Strategies
for Learning Questionnaire (MSLQ), which has been developed in 1991 Pintrich et al. (Pintrich et al.,
1990), and it is validated in various countries (Karadeniz et al., 2008). Motivation scale consists of 3 main
components for evaluation, i.e. : value, expectancy, affect (Liu & Lin, 2010). The instrument for
learning result is developed in multiple choice form with short answer, and it is grouped into 2
instruments i.e. instrument for measuring student's initial knowledge (by pretest), and instrument for
measuring learning results (by posttest).
Data analysis to be used in this research is rank two ANCOVA (Analysis of Covariance ) 2x2. This
research uses numerical variables with 2 factors that we want to know, i.e. (1) difference of mathematical
learning results for primary school students (posttest) between student group who use cooperative
learning game and not use game, (2) between student group who have high learning motivation and low
learning motivation for each treatment group. The steps for statisical test are as follows: 1) to check
Ancova test criteria, i.e.: normal distribution data, same data variance (homogen or equal variances);
2) to conduct rank two 2x2 variance analysis, in order to know the difference between average score of
mathematical learning results (posttest) in each student group who use cooperative learning game and not
use game, and group who have high learning motivation and low learning motivation; 3) post hoc test
analysis (Tukey Test), in order to know student treatment who use game and not use game of
cooperative learning, and have high and low learning motivation, which treatment causes the average
score of mathematical learning (posttest) tends to differ significantly or not.
RESULTS
The result of double comparison test (Tukey’s Test) between student group who learns using
cooperative learning game and not using it, by descriptive shows average score of learning result of
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student group who use cooperative learning game is 81.43, and it has significant difference if this
average score is compared to average score of student group who do not use game, i.e. 69.33 (Table 1).
Besides, the result of double comparison test (Tukey’s Test) for high learning motivation and low
learning motivation of students who use game and do not, it shows that the average score of learning
result between treatment group who have low learning motivation is 69.86, and it has significant
difference compared to average score of learning result between treatment group who have high learning
motivation, i.e. 77.76 (Table 2).
Table 1. Table showing difference of using game to learning result.
The average score of student group who use cooperative learning game and have low learning
motivation (experiment*low) is higher (average 74.67) compared to student group who do not use
cooperative learning game and have high learning motivation (Control *High) (average 71.8). And the
average score for student group who do not use cooperative learning game and have high learning
motivation (control *high) is relatively higher compared to average score of student group who do not
use cooperative learning game and have low learning motivation (control * low) (average 66.15) (Table
3).
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Table 2. Table showing difference of learning motivation to learning results.
Table 3. Table of learning output between treatment groups.
REFERENCES
Bright, G. W. 1985. Teaching Mathematics with Microcomputer Games. Journal of Educational
Computing Research, 1: 203-208.
Gee, J. P. 2003. What Video Games Have to Teach Us about Learning and Literacy. New York: Palgrave
Macmillan.
Imron, A. 1996. Belajar dan Pembelajaran. Jakarta : Dunia Pustaka Jaya.
Joyce, A., Gerhard, P., & Debry, M. 2009. How are Digital Games Used in Schools: Complete Results of
The Study. European Schoolnet.
Kebritchi, M. 2010. Factors Affecting Teachers' Adoption of Educational Computer Games: A Case
Study. British Journal of Educational Technology, 41(2), 256-270
Proceedings of the 14th International Conference on Media in Education 2016. Japan Association for Educational Media Study
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Kebritchi, M., & Hirumi, A. 2008. Examining the Pedagogical Foundations of Modern Educational
Computer Games. Elsevier, Computer & Education, 51:1729-1743.
Pintrich, R., Paul., & Elisabeth V. De Groot. 1990. Motivational and Self-Regulated Learning
Components of Classroom Academic Performance. Journal of Educational Psychology.
82(1):33-40.
McFarlane, A., Sparrowhawk, A., & Heald, Y. 2002. Report on The Educational Use of Games.
(Online).(http://www.teem.org.uk/), access: 12 September 2013.
Robinson, R., Molenda, M., & Rezabek, L. 2008. Facilitating Learning. Dalam A. Januszewski, & M.
Molenda (Eds.), Educational Technology: A Definition with Commentary (pp. 15-48). New York
& London: Lawrence Erlbaum Associates.
Slavin, R., E. 2010. Educational Psycology : Theory and Practice. Pearson Education, Inc.
Ulicsak, M., Wright, M., & Cranmer, S. 2009. Gaming in families: A literature Review. A Futurelab
report.
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