Thesis; Students Homework Motivation

Running Head: STUDENTS’ HOMEWORK MOTIVATION 1

Students’ Homework Motivation:

Adapting Homework Instruction to Students’ Characteristics

10-06-2013

Bianca Pater (3797538), Patrick Van Schaik (3906868), Lidy Van Den Tweel (3781240)

Bachelor thesis group 29

Department of Social Studies, Utrecht University

Supervisor: Dr. Chris Phielix

STUDENTS’ HOMEWORK MOTIVATION 2

Abstract

Lack of homework motivation is one of the problems mentioned concerning Dutch HAVO students.

A quasi-experiment is conducted, assuming homework motivation can be positively influenced by

adapting homework instruction to students’ characteristics. HAVO students in fourth grade of a Dutch

secondary school received homework instructions in an experimental way, using motivational

strategies that fit HAVO students’ characteristics. Effects on homework motivation were measured in

variables ‘expectancy’ and ‘value’. Data from 81 students, participating in four different school

subjects, reveals a significant increase in motivation which is mainly due to an increase of the

expectancy variable. Studying the effect on students’ motivation in separate subjects however, data

reflect differences. Students in the subjects mathematics and economy report significantly higher

expectancy and value levels, as students in history and chemistry report non-significant differences in

expectancy and value levels. Additionally the scores of all participating students were used to

determine whether pre-existing differences in HAVO characteristics ‘overall motivation’, ‘planning

skills’ and ‘student-teacher relationship’ had an effect on students’ homework expectancy and

homework value. Comparing groups of students with below average scores and above average scores

on characteristic scales reveals significant differences between these groups for characteristics

‘planning skills’ and ‘student-teacher relationship’ on homework expectancy levels. The results of

this study can be seen as an inspiration for teachers in HAVO 4 to find ways to increase their

students’ homework motivation. Teachers are advised to differentiate students or student groups on

their characteristics and to search for appropriate interventions on homework instruction. Researchers

recommend systematic research on homework instruction and homework motivation. Suggestions for

further research are given.

Keywords: characteristics, expectancy, HAVO student, homework, instruction, motivation, value


Students’ Homework Motivation

In 1998 the Dutch government introduces a major change in the general secondary

educational system of HAVO1 and VWO

2 students in the Netherlands, referred to as the introduction

of the Second Phase (Tweede Fase). The overall objectives of this change, ‘establish a better

connection of general secondary education to higher education’, and ‘modernization of the curriculum

in the upper general secondary education’, are widely accepted by professionals in the field of

education (Spijkerboer, Maslowski, Keuning, Van Der Werf, & Béguin, 2012). Nevertheless this

change entails increasing problems for HAVO students in fourth grade (Vermaas & Van Der Linden,

2007). The core problem mentioned is students’ lack of motivation. Problems are also attributed to

students’ lack of study skills, referring specifically to reflect, plan and work independently. In

addition, teachers apply a different teaching method in fourth grade, and have less personal contact

with students. All this results in poor grades, school failure, demotivated students and discouraged

teachers (Klomp & Thielen, 2010). In the past ten years research has been conducted into explicating

the various problems and doing proposals for solving them. A recurrent item in these reports is

homework and students’ homework attitude (Vermaas & Van Der Linden, 2007).

Vermaas and Van Der Linden (2007) conclude in their study ‘Better responding to HAVO

students’ that in need of problems mentioned - considering homework and motivation - education

must focus on the specific characteristics of HAVO students. School managers and teachers are

recommended to change the learning environment, so that it fits the profile of the HAVO student. An

elaboration into concrete recommendations regarding homework assignments is missing. The present

study focuses on homework and influencing students’ motivation for homework assignments by

adapting homework instruction to the specific characteristics of the HAVO students, and thereby

contributing in translating the overall conclusion of the report ‘Better responding to HAVO students’

to an operational level.

Research on homework

Homework is defined as “tasks assigned to students by school teachers that are meant to be

carried out during non-school hours” (Cooper, 1989). Problems regarding homework are not

1 HAVO = Higher General Secondary Education, a five year course, preparing students aged 12 – 17 years for higher or professional education. 2

VWO = Pre-university secondary education, highest variant in the secondary school educational system, six year course, preparing students aged 12 – 18 years for university.


restricted to HAVO students in the Netherlands. It is recognizable on an international level and has

been the subject of several studies. Homework purposes (Warton, 2001; Epstein & Van Voorhis,

2001; Xu, 2005), homework compliance (Cooper, 2006; Trautwein & Lüdtke, 2009), parental

involvement and learning environment (Hoover-Dempsey, Battiato, Walker, Reed, De Jong, & Jones,

2001), and achievement (Trautwein & Köller, 2003; Cooper, 2006) have been repeatedly studied and

show contradicting outcomes. As Corno (1996) states: “Homework is a complicated thing”,

explaining why the role of research in forming homework policies and practices is limited to a

minimum in comparison with other educational domains. Cooper (2006) explains this as a result of

the many complex influences on homework and the difficulties to generalize the outcomes in the

homework domain. One of these complex influences is motivation. Motivation directly influences

homework effort and homework effort is positively related to achievement (Trautwein & Lüdtke,

2009).

A homework model

Figure 1. Homework model – adapted version (Trautwein, Lüdtke, Schnyder, & Niggli, 2006).

Trautwein, Lüdtke, Schnyder, and Niggli (2006) conclude in their study about homework

compliance that students’ homework effort or homework behaviour is influenced by several variables

at the same time. They propose the use of a domain-specific, multilevel homework model. It takes

into account the three major protagonists in the homework process; teachers assigning homework,


parents providing the environment in which it is done, and finally students doing the homework, with

their unique profile of motivation and preference for learning (Hong & Milgram, 2000). The model

predicts homework behaviour to be positively related to achievement and influenced by homework

motivation with the components homework expectancy and homework value. These components are

in accordance with expectancy-value theory as described by Eccles and Wigfield (2002), and used in

this study to evaluate the effect of adapting homework instruction to students’ characteristics.

Motivation and expectancy-value theory

Motivation is an internal state that arouses, directs and maintains behavior (Woolfolk,

Hughes, & Walkup, 2013). There are several explanations for motivation. It can be explained in terms

of individual characteristics (personal traits), as a temporary situation (a state), or as a combination of

traits and state. Motivation generally refers to that which explains people’s desires and choices

(Keller, 2010). Doing homework starts with the question: ‘Am I going to do my homework?’

followed by ‘Why should I?’ (Keller, 2010). The answer depends on two forces: ‘Do I have a good

chance to succeed?’ (expectancy) and ‘Is the outcome valuable or rewarding to me?’ (value). The

modern expectancy-value theory (Eccles & Wigfield, 2002) is based in Atkinson’s (1957) work, and

explains motivational choices with an emphasis on individuals’ expectations for success in

combination with their valuing of the goal. Expectancies are defined as individuals’ beliefs about

competence in a given domain and one’s expectancies for success on a specific upcoming task. Task-

value is outlined in four components: attainment value – the personal importance of doing well on the

task, intrinsic value – the enjoyment the individual gets form performing the activity or the subjective

interest the student has in the subject, utility value - how well a task relates to current and future goals,

and costs – the negative aspects of engaging in the task as anxiety or fear, the amount of effort needed

to succeed and the lost opportunities that result from making a choice (Eccles & Wigfield, 2002).

ARCS model and motivational or instructional design

The ARCS model (Keller, 1987) provides a set of categories; attention, relevance, confidence,

and satisfaction, representing the components of motivation that correspond to the expectancy-value

theory (Atkinson, 1957; Eccles & Wigfield, 2002). Confidence generally refers to people’s

expectancies for success and beliefs regarding the degree to which they can predict or control the


outcomes of their behaviour. Value is represented by attention and relevance. Attention, in the context

of motivation, is a synthesis of several related concepts including curiosity, boredom, and sensation

seeking, and contains the attainment and intrinsic value components. Relevance refers to people’s

feelings or perceptions of attraction toward desired outcomes, ideas, or other people based upon their

own goals, motives, and values. Relevance contains the utility value, and costs component of

expectancy-value theory. Satisfaction, the outcome component of the ARCS model as a result of

effort, performance and consequences, illustrates that one’s actual experiences with the outcomes of a

goal oriented set of behaviors afterwards influences the value one attaches to that goal (Keller, 2010).

Keller’s ARCS model also includes sets of strategies to enhance motivation, and a systematic

design process for teachers to influence motivation. Influencing students’ motivation is considered to

be a challenge for teachers. Although it is impossible to control another person's motivation, much of

a teacher's job involves stimulating learners’ motivation. Learning environments, assignments,

instructional behavior and instructional design should ideally be designed towards this goal (Keller,

2010). Although the ARCS model is designed for broader use in instructional design, the model’s

strategies can be applied to enhance motivation to the smaller area of homework instruction.

A homework instruction model

Figure 2. Homework Instruction Model (Pater, Van Schaik, & Van Den Tweel, 2013)

Based on the homework model by Trautwein et al. (2006; see Figure 1), expectancy-value

theory (Eggles & Wigfield, 2002) and the ARCS model (Keller, 1987), the Homework Instruction


Model (Pater, Van Schaik, & Van Den Tweel, 2013) explains how adapting homework instruction

strategies to students’ characteristics can affect homework expectancy and homework value.

Attention, Relevance and Confidence cover the elements of the expectancy-value theory. Satisfaction,

the fourth component of Keller’s ARCS model, is not included in the Homework Instruction Model.

Effects on Satisfaction are influenced greatly by subjective evaluations of an outcome based on

expectations and social comparisons (Keller, 2010).

HAVO 4 students’ characteristics

An explanation for lack of (homework) motivation is sought in not taking into account

specific characteristics of HAVO 4 students. In order to adapt homework instruction to HAVO 4

students’ characteristics a closer look at these characteristics is required. Vermaas and Van Der

Linden (2007) composed a profile of HAVO students’ characteristics (see Figure 3) based on a study

among 50 schools that provide HAVO education. The profile is a representation of the characteristics

of the average HAVO 4 student, and shows the greatest common divisors. Pre-existing differences in

HAVO 4 students affect the premise of the research. To determine the influence of pre-existing

differences, the main problems in fourth grade of HAVO according to Klomp and Thielen (2010);

overall motivation, planning skills and student-teacher relationship, are taken into account in the

present study. These problems form the basis for the determination of the experimental interventions

to influence student’s homework motivation.

Figure 3. HAVO 4 students’ profile (Vermaas & Van Der Linden, 2007)

HAVO 4 students’ characteristics

a) Intelligent, creative, active and sociable,

b) Many activities beside school, less motivated for school – all day classes are boring;

c) Not knowing what they want to do after HAVO exams;

d) Focused on short term, lack of long-term focus on exams or further education;

e) Experiencing curriculum’s level of abstraction as too high, low relevance to authentic

experiences, preferring active and application-oriented learning;

f) Performance goal oriented, working harder for tests and exams;

g) Need for guidance and structure, lack of planning skills - postponing activities;

h) Short concentration curve;

i) Pragmatic, choosing the easiest way, responding to gaining points or free hours;

j) Responding to teachers’ attitude of involvement and individual contact;

k) Valuing social aspects: sensitive to the group process and their individual relationship to the

teacher.


Overall motivation corresponds to HAVO 4 student’s characteristic b) and f), referring to

students being less motivated for school in general and spending time on other activities beside

school. Motivation increases when tests or exams lie ahead. Planning skills corresponds to

characteristics d) and g), referring to beginning with homework assignments and learning for exams

and tests on time. Jolles (2007) suggests that planning problems are due to the inability to set

priorities, to balance between the imperative task of the teacher and the social cognitions about peer

pressure and implicit expectations that peers have of behavior. The adolescent is able to relatively

simple choices. But choices at a higher level means taking into account your own abilities, with the

consequences for the long term and with the desires or emotions of others. Problems experienced in

student-teacher relationships correspond to characteristics j) and k). They can be attributed to

organizational changes associated with the Second Phase (Vermaas & Van Der Linden, 2007).

Teachers in the first three grades of HAVO have a learner-centered approach, in the Second Phase

teachers show a more subject-orientated approach (Vermaas & Van Der Linden, 2007). HAVO 4

students indicate that they need individual time and attention of teachers and highly value the

relationship with the teacher (Klomp & Thielen, 2010).

The present study

The present study focuses on a better alignment between students’ characteristics and the

instruction of homework assignments, and measuring effects on homework expectancy and value. As

researchers we want to contribute to the body of knowledge about homework by focusing on a small

part of Trautwein’s homework model. The present study also wants to contribute in translating the

conclusions of the report ‘Better responding to HAVO-students” (Vermaas & Van Der Linden, 2007)

to an operational level by answering one of many teachers’ questions: “What can I do to motivate

students for doing their homework?” In this study we intend to inspire teachers by implementing

simple adaptions to homework instruction in the current daily process of assigning homework.

The effects of adapting homework instruction on the homework expectancy and homework

value of HAVO 4 students, taking into account the characteristics of HAVO 4 students, are explored

in a quasi-experiment. The study must give answers to the following research question: ‘What is the


effect on homework expectancy and homework value of HAVO 4 students when adapting homework

instruction to HAVO 4 students’ characteristics?’

Hypothesis 0: Adapting homework instruction to HAVO 4 students’ characteristics has no effect on

HAVO 4 students’ homework expectancy and homework value.

Hypothesis 1: Adapting homework instruction to HAVO 4 students’ characteristics has a positive

effect on HAVO 4 students’ homework expectancy and homework value.

Pre-existing differences lead to the following sub-questions and hypotheses: ‘What is the effect of

pre-existing differences in HAVO 4 students’ overall motivation, planning skills and/or student-

teacher relationship on the homework expectancy and homework of HAVO 4 students?’

Hypothesis 02: Pre-existing differences in HAVO 4 students have no effect on HAVO 4 students’

homework expectancy and homework value.

Hypothesis 2: Pre-existing differences in HAVO 4 students effect HAVO 4 students’ homework

expectancy and homework value.

Method

Research design

The experiment followed a 2 x 2 x 5 switching replications design. There were two levels of

measurements on homework motivation (homework expectancy and homework value) and two

conditions (traditional or control and experimental). The groups consisted of eight classes equally

divided over four subjects (chemistry, economics, history and math).

Figure 4. Switching replications design of the experiment.


The switching replications design is known as a very strong design with respect to internal

and external validity (Trochim, 2006). Main advantage is the possibility to correct on contingency

influences on the experiment. Caution should be exercised regarding the occurrence of an order effect.

Teachers of four subjects participated in this study, each one of them teaching two parallel

HAVO 4 classes. In the first phase one group was not given the experimental intervention and served

as control group (class X), and the other group (class Y) was given the experimental intervention. In

the second phase the experimental intervention switched to the other group (class X), and the original

group (class Y) served as control group. At the end of each phase both groups were tested on

homework motivation.

Participants

Students in HAVO 4 classes of the Calvijn College in Goes (n = 81) participated in this study.

Students came from Goes or smaller towns and villages in the area. The group of students included 41

young women between the age of 15 and 17 years (M = 15.85, SD = 0.58) and 40 young men between

15 and 17 years (M = 15.90, SD = 0.64). Some students (n = 26) participated in multiple courses.

Students (n = 10) participating but not finishing both measurements and students (n = 4) with a mean

score of 1.00 on one or both measurements were excluded.

Four teachers with parallel HAVO 4 classes at the Calvijn College voluntarily participated,

teaching in different subjects; chemistry, economics, history and mathematics.

Experimental intervention

The experimental intervention on homework instruction was designed to meet HAVO 4

students’ needs, fit their profile (see Figure 3), increase the motivation aspects, expectancy and (task-)

value as mentioned in expectancy-value theory (Eccles & Wigfield, 2002), and corresponded to the

conditions of attention, relevance and confidence in Keller’s ARCS model (Keller, 2010) (see Figure

2).

Attention. Instead of assigning homework at the end of the lesson, the teacher starts the

lesson with instruction on the upcoming homework assignment, and provides an immediate

connection to an overview of this of the subject and tests or exams (study planner). This part of the

intervention meets several HAVO 4 students’ characteristics, in particular b) and f) (see Figure 3).


Relevance. During the presentation of the new part of the curriculum the teacher connects

this lesson two times to the upcoming homework assignment. This part of the intervention meets

several HAVO 4 students’ characteristics, in particular d) and g) (see Figure 3).

Confidence. Instead of being able to choose when to start doing homework, the last ten

minutes of the lesson students all start with their assigned homework, while the teacher actively

answers individual questions and gives feedback to the students work. This part of the intervention

also meets several HAVO 4 students’ characteristics, in particular g), j) and k) (see Figure 3).

Instruments

In this quasi-experimental study four instruments were used: a questionnaire on students’

characteristics, a student- and teacher questionnaire on homework motivation, and an intervention

checklist (see Appendices A up to E). The first three measurements were assessed on a 5-point Likert-

type scale, with responses from ‘not true’, ‘a little true’, ‘sometimes true’, ‘true’ to ‘very true’. A

consistent scale format was selected for ease of administration and statistical analyses.

Student characteristics questionnaire. To determine the effect of pre-existing differences

between HAVO-students students filled in the Student Characteristics Scale (SCS; see Table 1),

measuring their overall motivation, planning skills and student-teacher relationship. The SCS was

offered to students three weeks prior to the experimental phases. Working with student numbers made

it possible to retrieve personal data from the database of the Calvijn College, including age and

gender.

Motivation. The subscale ‘motivation’ retrieved from the ‘Vragenlijst Studievoorwaarden’

(VSV; Crins, 2002), assesses the willingness to learn and do homework.

Planning Skills. The subscale ‘planning’ retrieved from VSV (Crins, 2002) assesses

beginning with homework assignments and learning for exams and tests on time.

Student-teachers relationship. The subscale ‘student-teacher-relationship’ contains adapted

questions from a previously conducted test, constructed by Calvijn College in Goes (2009) to assess

generally perceived teacher behavior in relation to the student.

Scores on the SCS (n =78) were used to determine whether pre-existing differences in

students in the subscales overall motivation, planning skills or student-teacher relationship had an


effect on students’ homework expectancy and homework value. Characteristic subscales were divided

in two groups based on the average score, named below average and above average, to create equal

sized groups and avoid underpowered, small sample sizes.

Table 1

Student Characteristics Scale (SCS)

Subscale Items Example item α

Motivation 9 “I work hard for tests or exams.” .70

Planning Skills 9 “I find it hard to keep me on my schedule.” .82

Student-Teacher Relationship 9 “My teachers encourage me to actively participate in the lesson.” .61

Student questionnaire on homework motivation. The student questionnaire Homework

Expectancy and Value Scale (HEVS) was constructed and adapted from Subject Interest Survey (CIS;

Keller, 2010) and Instructional Materials Motivation Survey (IMMS; Keller, 2010), including the

subscale ‘confidence’ for assessing the homework motivation component expectancy, and the

subscales ‘attention’ and ‘relevance’ for assessing homework motivation component value in students

(Table 2). Items were adapted to the specific homework conditions of HAVO 4 classes during the

experimental and non-experimental phase. Cronbach’s alpha for the 15-item HEVS was .90. For

Cronbach’s alphas on the subscales see Table 2.

Table 2

Homework Expectancy and Value Scale (HEVS)

Component Subscale Items Example item α

Homework expectancy Confidence 5 “The homework assigned this week is just too difficult for me” .75

Homework value

attainment value

intrinsic value

Attention 5 “There was something interesting at the beginning of lessons this week that got my attention”

.77

Homework value

utility value

costs

Relevance

5 “The instructor made the homework of this week seem important”

.80


Teacher questionnaire on homework motivation. The Perceived Homework Behavior

Questionnaire (PHBQ; see Table 3) gave teachers the opportunity to express their perceived and

experienced differences in students’ homework expectancy and homework value including

comparable questions to the students’ questionnaire based on the CIS (Keller, 2010) and IMMS

(Keller, 2010). Cronbach’s alpha for the 15-item PHBQ was .59. A closer examination of the

questionnaire item-total statistics indicated that alpha would increase to .67 after deleting 3 items one

by one. One item on expectancy, ‘I noticed that homework seemed important last week’ and two

items on value, ‘I paid attention on homework at the start of lesson for upcoming lesson’, and ‘I

contributed special attention towards homework this week’, were considered to be ambiguous and not

asking about the perceived homework behavior in students. Consequently these items were dropped

from the questionnaire, and subsequent analyses are based on teachers’ responses to the remaining

twelve items.

Table 3

Perceived Homework Behavior Questionnaire (PHBQ)

Component Subscale Items Example item

Homework expectancy Confidence 5 “This week I noticed that my students were well prepared for the lessons started”

Homework value Attention 5 “This week I succeeded in bringing the homework to the attention of the students”

Homework value Relevance 5 “This week I noticed that my students have recognized the importance of homework”

Intervention checklist. Teachers received an intervention checklist (see Appendix E) with a

summary of the intervention per lesson with experimental homework. The results of the intervention

checklist have been used to determine whether the teacher has performed the various parts of the

intervention as required (see Appendix F).

Procedure

Teachers and students received global information of the research that is conducted and all

participants remained anonymous. There was no financial compensation. Time for participating was


scheduled during students’ presence at school and data were collected during classes at the Calvijn

College. Whether a teacher volunteered in participating in this study determined the participation of

individual students or classes.

In week 12 the intervention was presented to the participating teachers in a manual, and

discussed this manual in week 13 in a one-to-one conversation with one of the researchers to check if

they understood and were able to perform the intervention.

In week 12 all 152 HAVO 4 students were invited to complete the digital students’

characteristics questionnaire (see Table 4) during classes in the computer lab, and were thereby

informed about the study on motivation in HAVO students that was about to take place in the fourth

grade at the Calvijn College. Students were unaware about the conditions they were assigned to.

Because interventions on homework were implemented by teachers, students may have been able to

recognize these interventions.

Table 4

Planning of measurements

Test Week Participants

Student Characteristics Scale 12 81 HAVO 4 students

Homework Expectancy and Value Scale, measurement 1

15

Students class X

Student class Y

Homework Expectancy and Value Scale, measurement 2

16 Students class X

Student class Y

Perceived Homework Behavior Questionnaire

15/16 Participating teachers

In week 15 for each participating subject, class X received the experimental intervention and

class Y got traditional homework (see Figure 4). At the end of week 15 HAVO 4 students in

participating subjects took the pencil-and-paper test on homework motivation during the last 5-10

minutes in class (see Table 4). In week 16 for each participating subject, class Y received the

experimental intervention and class X got traditional homework. At the end of week 16 all HAVO 4


students in participating subjects took the pencil-and-paper test on homework motivation during the

last 5-10 minutes in class.

In week 15 and 16 teachers completed the intervention checklist for lessons with experimental

homework. At the end of week 15 and 16 teachers were asked to fill in the PHBQ for classes X and

Y.

Data Analysis

Two separate databases were constructed for analysis in SPSS in order to meet the

assumptions for data analyses. In database A all participants in a subject (nsubjects = 107) are present. In

database B the participants (n = 26) who took part in multiple subjects were randomly assigned to one

of the four subjects (ntotal = 81).

To determine whether there has been an order effect an independent samples t test is done on

data classes X and classes Y.

To investigate the impact of the experimental intervention a one-way repeated measures

ANOVA was used on data of both conditions – traditional and experimental. A one-way ANCOVA

was used to compare homework motivation in students after the experiment undertaking four different

subjects (chemistry, economy, history and math). A covariate (students’ score on traditional

homework) was included to partial out the effects of participants’ homework motivation without the

interventions on homework. A MANOVA was used to examine the effectiveness of the interventions

on the two component of homework motivation - expectancy and value – in relation to the four

different subjects. One tailed paired sample t tests were used to compare homework expectancy or

homework value levels within the four subjects.

A descriptive analysis was performed on perceived homework motivation in students by

teachers, compared to homework expectancy and homework value levels perceived by students.

To determine the effect of pre-existing differences in HAVO 4 students’ characteristics, two-

tailed paired sample t tests were used to compare homework expectancy or homework value levels

within the characteristic groups. Repeated measures ANOVA with split-plots have been conducted to

compare the differences in homework expectancy or homework value between characteristic groups.


Results

Manipulation check

The switching replications design implicates that caution should be exercised regarding the

occurrence of an order effect. An independent samples t test was used to compare the differences on

the measurement score of participants (n = 40) receiving the experimental intervention in week 1 (M

= 0.11, SD = 0.55) and participants (n = 41) receiving the experimental intervention in week 2 (M =

0.31, SD = 0.77). The t test was non-significant, t(71.98) = 1.37, p = .174, two-tailed, d = 0.45, 95%

CI [-0.92, 0.50]. Absence of an order effect implicated that scores on students’ questionnaires on

measurement 1 and 2 can be combined and partitioned in test scores on traditional homework (or

control group) and test scores on experimental homework.

Homework motivation

A one-way repeated measures ANOVA was used to investigate the impact of the

experimental intervention. The repeated measures ANOVA indicates there is a significant increase on

homework motivation levels after the experimental intervention (M = 2.91, SD = 0.78) in comparison

with traditional homework (M = 2.71, SD = 0.74), F (1, 80) = 7.71, p = .007, partial η2 = .09.

Table 5

Summary of scores on measurements on HEVS in different subjects

Homework Motivation Homework Expectancy Homework Value

Traditional Experimental Traditional Experimental Traditional Experimental

Subject n M SD M SD M SD M SD M SD M SD

Chemistry 15 2.18 0.59 2.39 0.88 1.76 0.47 2.19 0.84 2.39 0.72 2.49 0.91

Economy 36 2.94 0.62 3.16 0.61 2.59 0.77 2.90 0.83 3.10 0.60 3.29 0.57

History 30 2.82 0.70 2.87 0.61 2.45 0.85 2.57 0.76 3.01 0.70 3.02 0.59

Math 26 2.92 0.76 3.27 0.60 2.65 0.80 2.87 0.68 3.05 0.77 3.48 0.64

Totala

81

2.71 0.74 2.91 0.78 2.32 0.80 2.61 0.82 2.90 0.77 3.06 0.82

Note. aNtotal = 81; chemistry (n = 14); economy (n=28); history (n = 19); mathematics (n = 18); 26 students participate in multiple

subjects.


Homework motivation per subject. A one-way ANCOVA was used to compare homework

motivation in students after the experiment undertaking four different subjects (chemistry, economy,

history and math). A covariate (score on traditional homework) was included to partial out the effects

of participants’ homework motivation without the interventions on homework. The ANCOVA

indicates that after accounting for the effects of traditional homework, there was a statistically

significant effect of the subject on homework motivation, F (3,76) = 4.48, p = .006, partial η2 = .150.

Post-hoc testing revealed that participants in economy and mathematics subject reported a higher

increase in homework motivation than students in chemistry class, even after controlling for

homework motivation measurement score on traditional homework. The remaining pairwise

comparisons were not significant.

Figure 5. Homework motivation levels per subject after traditional and experimental homework.

In order to compare scores on homework motivation in students in the traditional and

experimental condition within the various subjects, one-tailed paired sample t tests with an alpha level

of .05 were used. Participants (n = 26) previously assigned to one of the subjects for data analyses

were placed back in their original subjects. Expecting homework motivation to increase after the

intervention as stated in hypothesis 1, p values are divided by two. As Table 6 shows all scores on

homework motivation after the intervention were higher. Participants in the experimental condition of

the subjects chemistry (M = 2.39) and history (M = 2.87) reported higher homework motivation

levels, compared to participants in the control condition of chemistry (M = 2.18) and history (M =


2.82). However, these differences were not statistically significant for both chemistry, t(14) = 0.78, p

= .226, d = 0.29, and history, t(29) = 0.42, p = .340, d = 0.08. Participants in the experimental

condition in the subject economy reported significantly higher homework motivation levels (M =

3.16) compared to participants in the control condition (M = 2.92), who received traditional

homework, t(35) = 2.65, p = .006, d = 0.36. Also participants in the experimental condition in the

subject mathematics reported significantly higher homework motivation levels (M = 3.27) compared

to participants in the control condition (M = 2.92), who received traditional homework, t(25) = 3.13, p

= .002, d = 0.51.

Homework expectancy and homework value

A MANOVA was used to examine the effectiveness of the interventions designed to increase

homework motivation. Findings showed that there was a significant effect of the interventions on the

combined dependent variables homework expectancy and homework value F(1,159) = 3.08, p = .050,

η2 = .04. Analysis of the dependent variables individually showed non-significant effects for

homework value, F(1,160) = 1.08, p = .193, η2 = .01. However the homework expectancy variable

was statistically significant at a Bonferroni adjusted alpha level of .025, F(1,160) = 3.62, p = .021, η2

= .03. Participants in the experimental condition reported significantly higher homework expectancy

levels (M = 2.61) compared to participants in the control condition (M = 2.32), who received

traditional homework (see Figure 6).

Figure 6. Display of students’ scores on homework motivation divided in components expectancy and

value.


Homework expectancy per subject. One tailed paired sample t tests with an alpha level of

.05 were used to compare homework expectancy levels in different subjects in students in the control

condition, after receiving traditional homework and the experimental condition, after receiving the

intervention on homework. A summary of scores on measurements can be found in Table 5.

Figure 7 shows an increase in all subjects on homework expectancy. The participants reported

non-significant differences in homework expectancy levels in the experimental condition of the

subjects chemistry (M = 2.19), t(14) = 1.62, p = .064, d = 0.66 and history (M = 2.57), t(29) = 0.74, p

= .234, d = 0.15, compared to participant in the control condition of chemistry (M = 1.76) and history

(M = 2.45). Participants in the experimental condition in the subject economics reported significantly

higher homework expectancy levels (M = 2.90) compared to participants in the control condition (M =

2.59), who received traditional homework, t(35) = 2.83, p = .004, d = o.39. Also participants in the

experimental condition in the subject mathematics reported significantly higher homework

expectancy levels (M = 2.87) compared to participants in the control condition (M = 2.45), who

received traditional homework, t(25) = 1.73, p = .048, d = 0.30.

Figure 7. Homework expectancy levels per subject after traditional and experimental homework

Homework value per subject. One tailed paired sample t tests with an alpha level of .05

were also used to compare homework value levels in different subjects in students after receiving


traditional or experimental homework. A summary of scores on measurements can be found in

Table 5.

Figure 8 shows an increase in the subjects chemistry, economics and mathematics on

homework value and a minimal increase in history. The participants reported non-significant

differences in homework value levels in the experimental condition of the subjects chemistry (M =

2.49), t(14) = 0.34, p = .370, d = 0.12, and history (M = 3.02), t(29) = 0.09, p = .465, d = 0.02, in

comparison with the control condition of chemistry (M = 2.39) and history (M = 3.01). Participants in

the experimental condition in the subject economics reported significantly higher homework value

levels (M = 3.29) compared to participants in the control condition (M = 3.10), who received

traditional homework, t(35) = 1.91, p = .033, d = 0.32. Also participants in the experimental condition

in the subject mathematics reported significantly higher homework value levels (M = 3.48) compared

to participants in the control condition (M = 3.05), who received traditional homework, t(25) = 3.22, p

= .002, d = 0.61.

Figure 8. Homework value levels per subject after traditional and experimental homework.

Teachers’ perception of homework motivation

Teachers revealed a difference in perceiving homework behavior in different classes. Results

shown are descriptive and were not statistically analyzed, as it concerned the comparison between a


single teacher and his or her classes (see Table 6). Only notable resemblances and differences are

mentioned.

Table 6

Teacher Perceptions versus Student Perceptions Concerning Students’ Homework Expectancy and Value

Expectancy Value

Teacher Students Teacher Students

T E T E T E T E

Subject Class M M M M M M M M

Chemistry X 1.80 3.20 1.63 2.38 2.60 3.60 2.23 2.53

Chemistry Y 3.00 1.80 2.24 2.66 3.80 3.00 2.47 2.06

Economy X 2.60 3.40 2.47 2.81 2.40 3.60 3.09 3.18

Economy Y 2.80 3.60 2.57 2.88 2.40 4.00 2.97 3.33

History X 3.00 3.20 2.62 2.60 2.40 2.40 3.19 3.19

History Y 3.40 3.00 2.24 2.66 3.00 2.80 3.04 2.95

Mathematics X 2.40 2.20 2.60 2.87 3.60 3.40 2.96 3.58

Mathematics Y 2.60 3.00 2.49 2.69 3.20 3.80 3.22 3.49

Note. T=traditional homework; E=experimental homework; X=experimental homework in second week; Y=experimental

homework in first week.

Teachers assign different scores to classes X and Y. A remarkable difference in perception is

found in classes X and Y in chemistry, and to a lesser extent in history. Students in chemistry classes

confirm these differences in their scores, but are more moderate. Student scores in history classes X

and Y show a different pattern than their teacher’s scores.

Teachers’ and students’ scores are not always consistent. In economy, teacher en students’

scores are quite consistent, but students initially value their homework more than the teacher

perceived. Inconsistent scores were found for example in mathematics class X. The teacher perceived

a drop in homework motivation in both expectancy and value, while students showed in increase on

both motivation components. The history teacher perceived opposite effects in homework expectancy

than students did in both classes. Finally teachers in general showed greater differences in perception

after the experiment than students revealed.


Effect of pre-existing differences on homework expectancy levels per characteristic

Multiple two-tailed paired sample t tests were used to compare homework expectancy levels

in below average and above average groups per characteristic after traditional and experimental

homework (see Table 7).

Table 7

Homework Expectancy Levels in Students with Below and Above Average Scores on Characteristic

Homework Expectancy

Traditional Experimental

Characteristic Groupb

n M SD M SD Δa

t p d

Overall motivation

Below < 2.80 43 2.31 0.64 2.61 0.75 0.30 -2.46 .018* 1.45

Above > 2.80 35 2.33 0.98 2.58 0.91 0.25 -1.83 .076 0.26

Planning skills

Below < 2.95 40 2.11 0.63 2.47 0.76 0.36 -3.04 .004* 0.52

Above > 2.95 38 2.54 0.92 2.74 0.87 0.20 -1.42 .164 0.22

Relationship with teacher

Below < 2.99 33 2.07 0.69 2.33 0.79 0.26 -2.40 .022* 1.08

Above > 2.99 45 2.49 0.85 2.79 0.80 0.30 -2.12 .039* 0.36

Note.*Significant higher homework expectancy level after the intervention (p < .05) within the characteristic ; aΔ = experimental

- traditional. bScore computed with scores on SCS.

Overall motivation. Participants with below average overall motivation reported

significantly higher homework expectancy levels (M = 2.61) receiving experimental homework than

after receiving traditional homework (M = 2.31), t(42) = -2.46, p = .018, d = 1.45. Participants with

above average overall motivation reported non-significant differences in homework expectancy levels

after receiving experimental homework (M = 2.58) in comparison with receiving traditional

homework (M = 2.33), t(34) = -1.83, p = .076, d = 0.26 (see Table 7). The split-plot repeated

measures indicated that there was no difference between the below and above average overall

motivation group in homework expectancy, F(1,76) =0.00, p = .995, η2 = .00 (see Figure 9).


Planning skills. Participants with below average planning skills reported significantly higher

homework expectancy levels (M = 2.47) receiving experimental homework than after receiving

traditional homework (M = 2.11), t(39) = -3.04, p = .004, d = 0.52. Participants with above average

planning skills reported non-significant differences in homework expectancy levels after receiving

experimental homework (M = 2.74) in comparison with receiving traditional homework (M = 2.54),

t(37) = -1.42, p = .164, d = 0.22 (see Table 7). The split-plot repeated measures indicated that there

was a significant difference between the below and above average planning skills group in homework

expectancy, F(1,76) =4.95, p = .026, η2 = .06 (see Figure 9).

Figure 9. Means on homework expectancy levels after traditional and experimental homework for below and

above average groups on characteristics scale; overall motivation; planning skills and student-teacher

relationship. Y axis starts with 2 because all homework expectancy levels are located between 2.0 and 3.0; the

graph is intended to show the differences between the groups.

Student-teacher relationship. Participants with below average student-teacher relationship

reported significantly higher homework expectancy levels (M = 2.33) receiving experimental

homework than after receiving traditional homework (M = 2.07), t(32) = -2.40, p = .022, d = 1.08.

Participants with above average student-teacher relationship also reported significantly higher

homework expectancy levels (M = 2.79) receiving experimental homework than after receiving

●Below Overall Motivation

○Above Overall Motivation

Below Planning Skills

Above Planning Skills

■Below Student-Teacher Relationship

□Above Student-Teacher Relationship


traditional homework (M = 2.49), t(44) = -2.12, p = .039, d = 0.36 (see Table 7). The split-plot

repeated measures indicated that there was a significant difference between the below and above

average student-teacher relationship group in homework expectancy, F(1,76) =7.81, p = .007, η2 = .09

(see Figure 9).

Effect of pre-existing differences on homework value levels per characteristic

Multiple two-tailed paired sample t tests were used to compare homework value levels in below

average and above average groups per characteristic after traditional and experimental homework (see

Table 8).

Table 8

Homework Value Levels in Students with Below and Above Average Scores on Characteristic

Homework Value

Traditional Experimental

Characteristic Groupb n M SD M SD Δ

a t p d

Overall motivation

Below < 2.80 43 2.89 0.62 3.05 0.70 0.16 -1.71 .094 0.24

Above > 2.80 35 2.91 0.95 3.08 0.98 0.17 -1.20 .240 0.17

Planning skills

Below < 2.95 40 2.83 0.73 2.93 0.68 0.10 -0.94 .351 0.14

Above > 2.95 38 2.97 0.84 3.21 0.95 0.24 -1.87 .070 0.27

Relationship with teacher

Below < 2.99 33 2.77 0.74 2.82 0.78 0.05 -0.45 .654 0.06

Above > 2.99 45 2.98 0.80 3.24 0.83 0.26 -2.18 .034* 0.32

Note.*Significant higher homework value level after the intervention (p < .05) within the characteristic; aΔ = experimental -

traditional. bScore computed with scores on SCS.

Overall motivation. Participants with below average overall motivation reported non-

significant differences in homework value levels after receiving experimental homework (M = 3.05)

in comparison with receiving traditional homework (M = 2.89), t(42) = -1.71, p = .094, d = 0.24.

Participants with above average overall motivation also reported non-significant differences in

homework value levels after receiving experimental homework (M = 3.08) in comparison with


receiving traditional homework (M = 2.91), t(34) = -1.20, p = .240, d = 0.17 (see Table 8). The split-

plot repeated measures indicated that there was no difference between the below and above average

overall motivation group in homework value, F(1,76) =0.02, p = .895, η2 = .00 (see Figure 10).

Planning skills. Participants with below average planning skills reported non-significant

differences in homework value levels after receiving experimental homework (M = 2.93) in

comparison with receiving traditional homework (M = 2.83), t(39) = -0.94, p = .351, d = 0.14.

Participants with above average planning skills also reported non-significant differences in homework

value levels after receiving experimental homework (M = 3.21) in comparison with receiving

traditional homework (M = 2.97), t(37) = -1.87, p = .070, d = 0.27 (see Table 8). The split-plot

repeated measures indicated that there was no difference between the below and above average

planning skills group in homework value, F(1,76) =1.76, p = .188, η2 = .02 (see Figure 10).

Figure 10. Means on homework value levels after traditional and experimental homework for below and above

average groups on characteristics scale; overall motivation; planning skills and student-teacher relationship. Y

axis starts with 2.5 because all homework value levels are located between 2.5 and 3.5; the graph is intended to

show the differences between the groups.

●Below Overall Motivation

○Above Overall Motivation

Below Planning Skills

Above Planning Skills

■Below Student-Teacher Relationship

□Above Student-Teacher Relationship


Student-teacher relationship. Participants with below average student-teacher relationship

reported non-significant differences in homework value levels after receiving experimental homework

(M = 2.82) in comparison with receiving traditional homework (M = 2.77), t(32) = -0.45, p = .654, d =

0.06. Participants with above average student-teacher relationship reported significantly higher

homework value levels (M = 3.24) receiving experimental homework than after receiving traditional

homework (M = 2.989), t(44) = -2.18, p = .034, d = 0.32 (see Table 8). The split-plot repeated

measures indicated that there was no difference between the below and above average student-teacher

relationship group in homework value, F(1,76) =3.78, p = .056, η2 = .05 (see Figure 10).

Conclusion and discussion

First, the present study found empirical support for a positive effect on homework motivation

of HAVO 4 students, when adapting homework instruction to HAVO 4 students’ characteristics as

presumed in hypothesis 1. Results show significantly higher homework expectancy levels after the

intervention. Non-significant results were found for the homework value component. Looking closer

at the four different subjects participating in this study, homework expectancy levels and homework

value levels are significantly higher in both economy and mathematics after the intervention took

place. This could be explained by the fact that teachers in the subjects mathematics and economy

performed the experimental intervention almost as accurately as they were presented to them. But

different contents of the subjects can also contribute to the non-significance of chemistry and history.

Differences in expectancy and value levels between subjects are consistent with Trautwein et al.

(2006), promoting a domain-specific approach of homework. In their studies on homework

motivation a considerable variability in the perception of homework was found between subjects:

Mathematics homework scores lower on component expectancy than English homework, for the

value component this is reversed. Variables appear to make a difference in predictive value per

subject (Trautwein et al., 2006). Several other studies have been conducted on the effect of

motivational design strategies (Keller, 2010), generally focusing on instructional design for face-to-

face, computer-basis or blended courses. Most of them subscribe a positive effect on motivation

components (Visser & Keller, 1990; Song & Keller, 2001; Colakoglu & Akdemir, 2010). A study on

the effect of ARCS-based strategies with specific attention for the expectancy component (Huett,


Moller, Young, Bray, & Huett, 2008) did not produce a noted increase in learner confidence, but did

find an effect in overall motivation of students for their specific subject. This confirms the starting

point of this study, dividing motivation in at least two components. Each component can be

experimentally influenced in its own way, and measured as a separate variable. Point of attention is

that variables might influence each other. Besides the differences between the subjects, the short

period of the experimental intervention in this study could have caused faster results on homework

expectancy, students being confident in their ability in doing the assigned homework tasks, rather than

increasing students’ value on homework tasks as relevant and having their attention.

Second, hypothesis 2 stated that pre-existing differences ‘overall motivation’, ‘planning

skills’ and ‘student-teacher relationship’ would have an effect on HAVO 4 students’ homework

expectancy and homework value levels. Results of this study do reveal that dividing students in two

groups, based upon their below or above average score on a student characteristic, has different effect

on their scores on homework expectancy and homework value. All three groups scoring below

average on overall motivation, planning skills and student-teacher relationship show significantly

higher homework expectancy levels after the intervention took place. Only the above average student-

teacher relationship group also scored significantly higher after the intervention. This could mean that

having a good or less good relationship with your teacher has no effect on your homework

expectancy. But as Figure 9 reveals, it seems that no matter what your characteristics are, homework

expectancy will increase almost equivalent in all groups after the intervention. Although only the

above average student-teacher relationship group shows significantly higher levels of homework

value after the intervention, Figure 10 shows a different pattern in slopes as seen in homework

expectancy. Homework value levels after traditional homework start initially higher than homework

expectancy levels, but show a clear difference in increase between groups after the intervention. An

explanation can be given by stating that an intervention must connect to the initial level of a student,

and only then a student will profit from this ‘push in the right direction’. This has a positive impact on

the expectancy and/or value component of motivation. When an intervention is not connected to

students’ initial level a student can experience the intervention as incomprehensible or superfluous,

showing no effects on motivation or possibly even demotivating a student. In this study it seems the


part of the intervention designed to increase homework value levels is more in line with

characteristics of students in the above average groups. Anticipating on the wide range of individual

differences among students is consistent with Hong, Milgram, and Rowell (2010). Teachers should

encourage learners to match their preferences on doing homework with the actual situation, resulting

in higher motivation levels. This recommendation can be easily transformed to teachers being

encouraged to match their students’ characteristics.

Screening students on their pre-existing differences created awareness of the fact that each

individual student has a different set of characteristics. Interpreting the HAVO students’ profile

(Vermaas & Van Der Linden, 2007) as a blueprint of the average HAVO student, contains a risk of

not taking into account the individual differences of HAVO students and must be prevented by

researchers at any time. HAVO 4 is a composition of several groups of students (Vermaas & Van Der

Linden, 2007), with different sets of characteristics. Instead of giving all students the same treatment,

based upon the HAVO 4 students’ profile, individuals or groups of students should receive a

treatment adapted to their specific set of characteristics.

Limitations of the study

This study has been conducted on one Dutch secondary school. The HAVO-department

received the title of ‘Excellent School’ in 2012, referring to high quality of education and being an

example for other schools. Much attention is paid to an individual approach and guidance of each

student. This could have influenced the results.

Doing social research on a secondary school is a complicated process (Cooper & Valentine,

2001). The initial scope of our sample was 152 HAVO-students. Due to unexpected circumstances the

sample had to be reduced. Given the restricted number of students in the present study,

generalizability is an issue. A number of students participated in experimental classes in more than

one subject. This could have influenced the results, either in a positive or negative way. Another

reason to be cautious in generalizability is the influence of the individual teachers on performing the

experimental interventions. Although all teachers received the same instructions and there was control

of performing the parts of the intervention, there was no control of the manner in which the

instructions were performed.


Two other important factors on influencing homework motivation were no part of this study

and therefore need mentioning as limitations: the composition of students in one class, and the

characteristics of an individual teacher. In our study we recognize the differences in scores on

homework motivation in classes X and Y within a subject, and this might have influenced the final

scores on homework motivation. No attention was paid to the individual differences of teachers’

characteristics and their personal influence on students’ motivation. In their review of research on the

relationship between teachers characteristics and students’ achievement Wayne and Youngs (2003)

confirm the existence of a positive relationship, but it needs further research to be more specific.

Evaluating the present research the choice for the switching replications design was made,

because of its high internal validity (Trochim, 2006). The external validity is limited due to the

limited size of the sample. The student- and teacher questionnaire, developed for this study, scored

high on reliability. To promote a broader range in answers, a 7-point- instead of a 5-point Likert scale

is recommended in future research. The Student Characteristics Scale was partly reliable. Subscale

‘student-teacher relationship’ should be interpreted with caution because of the mediocre reliability.

Although the experimental interventions were matched to the amount of time available, the

time component makes it only possible to draw conclusions on the short term. To improve external

validity and draw conclusions for the long term, expanding the experimental period is recommended.

Further research

The limited quasi experiment in this study reveals a surprising positive effect of adapting

homework instruction on students’ characteristics to improve homework motivation. Results not only

contribute to the body of knowledge on homework and homework motivation in general, but can also

contribute in the attempts to tackle the existing problems in motivation of HAVO students in the

Netherlands. Drawing teachers’ attention to the results of this study can convince teachers that they do

have influence on students’ motivation, even by doing small interventions. Their perceptions of

motivation do not necessarily correspond to the experience of the student. Anticipating on student’s

characteristics, interventions can be done on both individuals and groups.

In line with this study, further research is recommended on ways of homework instruction to

influence homework motivation, using larger samples of students in different schools and thereby


making research results more generalizable and answer questions such as; ‘Which interventions on

homework instruction motivates students?’ and ‘To what extent is domain-specific approach of

importance of the adaptation of homework instruction?’. Further research can be done on the

application of the HAVO students’ profile in daily practice; ‘Is it possible to develop sets of

characteristics for the different groups of students in HAVO 4, and are teachers able to motivate

students by adapting homework instruction to these specific set of characteristics?’ or ‘Is the HAVO

student served by a more individual approach tailored to his or her individual profile?’

Corno (1996) stated that homework is a complicated thing. Aligning ourselves with the

general recommendation that research on homework instruction and homework motivation needs to

be extended, specific recommendations are made to work from one general model in which variables

get their place. Trautwein’s homework model (Trautwein et al., 2006) could be used as a starting

point. Systematic research, resulting in a further perfection of the homework model contributes to an

increasing knowledge base. Eventually all of this can lead to an influence of homework research on

policy and practice (Cooper & Valentine, 2001).


References

Atkinson, J. M. (1957). Motivational determinants of risk-taking behaviour. Psychological Review 65,

359-372.

Colakoglu, O., Akdemir, O., & Eregli, K. (2010). Motivational measure of the instruction compared:

Instruction based on the ARCS motivation theory vs traditional instruction in blended

courses. Retrieved from Turkish Online Journal of Distance Education, 11(2), 73-89.

Cooper, H. (1989). Homework. White Plains, NY: Longman.

Cooper, H., & Valentine, J.C. (2001). Using Research to Answer Practical Questions About

Homework. Educational Psychologist 36(3), 143–153. Retrieved from http://web. ebscohost.

com

Cooper, H., Robinson, J. C., & Patall, E. A. (2006). Does homework improve academic achievement?

A synthesis of research, 1987 – 2003. Review of Educational Research 76(1), 1-62.

doi:10.3102/00346543076001001

Corno, L. (1996). Homework is a complicated thing. Educational Researcher 25(8), 27-30.

doi:10.3102/0013189X025008027

Crins, J. (2002). Vragenlijst Studievoorwaarden (VSV). KPC groep. ’s-Hertogenbosch.

Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of

Psychology 53, 109-132. doi:10.1146/annurev.psych.53.100901.135153

Epstein, J. L., & Van Voorhis, F. L. (2001). More than minutes: Teachers’ roles in designing

homework. Educational Psychologist 36(3), 181–193. doi:10.1207/S15326985EP3603_4

Hong, E., & Milgram, R. M. (2000). Homework: Motivation and learning preference. Praeger Pub

Text.

Hoover-Dempsey, K. V., Battiato, A. C., Walker, J. M., Reed, R. P., DeJong, J. M., & Jones, K. P.

(2001). Parental involvement in homework. Educational Psychologist, 36(3), 195-209.

doi:10.1207/S15326985EP3603_5

Huett, J. B., Moller, L., Young, J., Bray, M., & Huett, K. C. (2008). SUPPORTING THE DISTANT

STUDENT The Effect of ARCS-Based Strategies on Confidence and Performance. Retrieved

from Quarterly Review of Distance Education 9(2), 113-126


Jianzhong, X. U. (2005). Purposes for doing homework reported by middle and high school students.

The Journal of Educational Research, 99(1), 46-55. doi: 10.3200/JOER.99.1.46-55

Keller, J. M. (2010). Motivational design for learning and performance: The ARCS model approach.

Springer.

Keller, J. M. (1987). Development and use of the ARCS model of instructional design. Journal of

instructional development, 10(3), 2-10. doi: 10.1007/BF02905780

Klomp, J., & Thielen, S., (2010). Bovenbouw havo problematiek: Project in het kader van LD

Verbreding ‐Verdieping. Ruud de Moor Centrum / OUNL i.s.m. Orion. Retrieved from Open

Universiteit website: http://www.ou.nl/documents/14300/6dc40eca-8fb9-4964-8838-

dd1939701cbc

Song, S. H., & Keller, J. M. (2001). Effectiveness of motivationally-adaptive computer-assisted

instruction on the dynamic aspects of motivation. Educational Technology Research &

Development, 49(2), 5 - 22. doi:10.1007/BF02504925

Spijkerboer, A. W., Maslowski, R., Keuning, J., Van Der Werf, M. P. C., & Béguin, A. A. (2012).

Evaluatie van de nieuwe wetgeving voor de Tweede Fase havo/vwo. Gronings Instituut voor

Onderzoek van het Onderwijs. Retrieved from Rijks Universiteit Groningen website:

http://gion.gmw.eldoc.ub.rug.nl/FILES/root/2012/Evaluatiehavo/Evaluatiehavo.pdf

Trautwein, U., & Lüdtke, O. (2009). Predicting homework motivation and homework effort in six

school subjects: The role of person and family characteristics, classroom factors, and school

track. Learning and instruction 19(3), 243-258. doi:10.1016/j.learninstruc.2008.05.001

Trautwein, U., Lüdtke, O., Schnyder, I., & Niggli, A. (2006). Predicting homework effort: support for

a domain-specific, multilevel homework model. Journal of Educational Psychology 98(2),

438-456. doi:10.1037/0022-0663.98.2.438

Trautwein, U., & Köller, O. (2003). The relationship between homework and achievement—Still

much of a mystery. Educational Psychology Review, 15(2), 115-145. doi:1040-726X/03/

0600-0115/0

Trochim, W.M.K. (2006). Research methods knowledge base. Retrieved from Socialresearchmethods

website: http://www.socialresearchmethods.net/kb/index.php


Vermaas, J., & Van der Linden, R. (2007). Beter inspelen op havo-leerlingen. IVA

beleidsonderzoek en advies, Tilburg. Retrieved from Kortlopend Onderwijsonderzoek

website: http://www. kortlopendonderzoek.nl/documenten/beter%20inspelen%20

havoleerlingen.pdf

Visser, J. & Keller, J. M. (1990). The clinical use of motivational messages: an inquiry into the

validity of the ARCS model of motivational design. Instructional Science, 19, 467–500.

doi:10.1007/BF00119391

Warton, P. M. (2001). The forgotten voices in homework: Views of students. Educational

Psychologist, 36(3), 155-165. doi:10.1207/S15326985EP3603_2

Woolfolk, A. E., Hughes, M., & Walkup, V. (2007). Psychology in education. Pearson Education.


Appendix A

Instruments - Student Characteristics Scale (SCS)

Student Characteristics Scale – 27 items 5-point Likert-schaal Motivatie (9 items, subschaal VSV)

Code Volgorde Item

M1 1 Ik doe bepaalde dingen extra voor mijn studie, ook als daar niet om wordt gevraagd.

M2 2 Ik ga naar school om te leren.

M3 6 Ik leer alleen omdat het moet. REVERSE

M4 9 Ik maak graag huiswerk.

M5 16 Ik werk hard voor een overhoring of een proefwerk.

M6 18 Leren komt bij mij op de tweede plaats. REVERSE

M7 19 Ik kijk of leerstofonderdelen uit een hoofdstuk met elkaar verband houden.

M8 23 Wanneer ik een proefwerk of toets terugkrijg, kijk ik na welke fouten ik heb gemaakt en probeer hier iets van te leren.

M9 25 Ik wil meer weten van de stof dan de leraar vraagt.

Planningsvaardigheden (9 items, gebaseerd op subschaal VSV)

P1 3 Aan het begin van de week maak ik een verdeling van mijn huiswerk over de week.

P2 5 Een toets of proefwerk leer ik meerdere malen.

P3 10 Voordat ik begin met mijn huiswerk bepaal ik de volgorde waarin ik dit ga maken.

P4 11 Van tevoren schat ik in hoeveel tijd ik nodig heb voor het uitvoeren van een huiswerkopdracht.

P5 13 Ik houd rekening met onvoorziene omstandigheden en daarom bouw ik reservetijd in bij het studeren voor een toets of proefwerk.

P6 15 Ik vind het lastig me aan mijn eigen planning te houden. REVERSE

P7 21 Op dagen dat ik niet veel huiswerk heb, begin ik aan het huiswerk van een zware dag.

P8 24 Ik begin te laat met het leren van een proefwerk of een toets. REVERSE

P9 27 Voor een toets of proefwerk houd ik tijd vrij om de leerstof nog eens extra te kunnen herhalen.

Relatie docent (gebaseerd op vragenlijst Calvijn College)

R1 4 Ik voel me op mijn gemak bij mijn docenten.

R2 7 Ik heb nauwelijks persoonlijk contact met mijn docenten. REVERSE

R3 8 De docenten geven duidelijk antwoord op vragen over de leerstof en het huiswerk.

R4 12 De docenten moedigen mij aan om actief mee te doen in de les.

R5 14 Mijn docenten zijn enthousiast en betrokken.

R6 17 Docenten bespreken regelmatig met ons hoe we werken en wat we daarmee bereiken.

R7 20 Mijn docenten doen er alles aan om mijn prestaties te helpen verbeteren.

R8 22 Docenten houden zich aan de afspraken die ze met ons maken.

R9 26 Mijn docenten weten nauwelijks iets van mijn leven buiten schooltijd. REVERSE


Appendix B

Instruments – Homework Expectancy and Value Scale (HEVS)


Appendix C

Instruments – Perceived Homework Behaviour Questionnaire (PHBQ)


Appendix D

Instruments – Accountability check on HEVS and PHBQ

Vragen voor Huiswerk Belevingsschaal Confidence 1. Tijdens het maken van het huiswerk deze week had ik het gevoel goed bezig te zijn met dit vak.

2. Ik denk dat mijn leraar vindt dat ik mijn huiswerk goed gemaakt heb deze week.

3. Mijn leraar heeft laten merken hoe ik deze week mijn huiswerk heb gemaakt.

4. Door de uitleg van het huiswerk geloofde ik dat ik het huiswerk zelf kon maken.

5. Door de manier waarop de leraar het huiswerk toelichtte wist ik wat ik zou moeten leren van dit huiswerk Attention 1. Mijn leraar heeft me in de afgelopen week enthousiast gemaakt voor het huiswerk.

2. Er was iets aan het begin van de lessen wat mijn aandacht voor het huiswerk trok deze week. 3. Ik was deze week nieuwsgierig naar het huiswerk voor dit vak

4. De docent heeft op een ongewone of verassende manier aandacht gegeven aan het huiswerk

5. Door de manier waarop het huiswerk werd uitgelegd, werd mijn aandacht op het huiswerk gericht. Relevance 1. Het huiswerk voor dit vak was de afgelopen week was voor mij zinvol.

2. De leraar zorgde ervoor dat het huiswerk van deze week belangrijk leek

3. Ik ben de afgelopen week actief bezig geweest met maken van huiswerk tijdens de les.

4. Het huiswerk van deze week was belangrijk om een goed een cijfer voor dit vak te kunnen halen.

5. Het huiswerk van de afgelopen week sloot goed aan bij de inhoud van de les.


Appendix E

Instruments – Intervention Checklist


Appendix F

Results on Teacher Intervention Checklist

Table F1

Teacher Intervention Checklist

Intervention

Start During End

Subject Lesson

Instruction on upcoming homework

Provide connection to

curriculum Connect content

to homework

Provide relevance, short

+ long term

Homework start at the last ten

minutes

Active rol teacher, provide

feedback

Chemistrya

Class X 1 + + + + + + 2 + + + + + +

Class Y 1 + + + + + + 2 + + + + + +

Economy Class X 1 + + + + - -

2 + + + + + + 3 + + + + + +

Class Y 1 + + + + - - 2 - + + + + + 3 + + + + + +

History Class X

b 1 + + + + + +

2 + + - + + + 3 + - - - - -

Class Y 1 + + + + + + 2 + + + + + + 3 + + + + + +

Math Class X 1 + + + + + +

2 + + + + + + 3 + + + + + +

Class Y 1 + + + + + + 2 + + + + + + 3 + + - - + +

Note. + = intervention performed; - = intervention not performed. aOnly two lessons given during the experimental week.

bTrainee conducted

lessons not satisfactorily according to teacher.

Documents

Thesis; Students Homework Motivation