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Motivational strategies of students in Virtual University

Anne Nevgi Department of Education

University of Helsinki A paper to be presented in Evidence-Based Policies and Indicator Systems Third International Inter-disciplinary conference 4.-7.July 2001, University of Durham,

England

Introduction This paper discusses the role of virtual university students' motivational strategies for

learning. The paper is based on a study, which is part of a larger IQ-FORM research

project (WWW-site http://www.edu.helsinki.fi/iqform/). First is presented the aim and

the theoretical background of IQ FORM research project and then is introduced

theoretical framework for motivational strategies. In order to validate and develop the

measurement tool for Motivational learning strategies of Virtual Unversity students’

the pilot study was taken in January 2001. The data of pilot study and the validation

procedures of factorial structure of the measurement are presented and the effect of

tutorial guidance to the students’ motivational strategies is demonstrated.

IQ FORM research project IQ FORM research project began at the end of 1999 and it is a co-operative project

with educational, computing and information technology sciences involved. The aim

of the project is to develop tools for virtual university students to help them become

more effective learners of virtual university.

The main tasks of the project:

• The project will explore how different learners study in virtual environments

and what kind of support they would need.

• The project has been developing a flexible IQ FORM data bank, which will be

used during 2001 in virtual university courses.

• The project is also developing a tutorial package, which can be adapted

according to the needs of specific courses, students and teachers. (IQ-FORM

research team, http://www.edu.helsinki.fi/iqform/)

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The Project Director is Professor Hannele Niemi, Dean of the Faculty of Education at

the University of Helsinki. The researchers of the IQ-FORM project are mainly from

University of Helsinki but they have co-operation and networking partners in

universities of Oulu, Tampere and Joensuu, which will apply new learning and

tutoring tools in their virtual courses.

The theoretical framework behind IQ-FORM is based on theories of mediated

learning, distributed cognition, and on Gardner’s multiple intelligence theory

(Gardner 1983) and Pintrich & Ruohotie’s motivational theory (Ruohotie & Pintrich

2000). A social navigation in virtual learning environments is discussed as an

empowerment of student learning (Niemi 2001).

IQ-FORM tools for learners

The main tool to help the learner is called IQ-FORM (intelligent questionnaire), an

interactive databank. IQ-FORM gives information about the qualities of students as

learners e.g. learning profiles and motivational structures as social navigation during

their virtual studies (Niemi 2000a). The questionnaires work as a data bank, from

which students may select different combination to become more conscious of their

learning styles and motivational strategies and changes in these qualities during the

course (IQ-Research group 2001a and IQ-Research group 2001b). The profiles, which

are based on the tests, tutor the students to find help and support from their teachers or

peers and to encourage them to use new kind of learning material or routes to find

more effective learning strategies.

The other tool, or set of tools consists of a tutoring package for learners and teachers.

This package contains guidance packages for students, student groups (in specific

virtual classes) and teachers. The student packages will lead the student for example

to analyze their learning styles, strengths and weaknesses and help them, when a

problem situation occurs.

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Motivational strategies for learning in IQ-FORM In this paper the focus is on the motivational strategies of students and a theoretical

background is based on a theory presented by Pintrich and Ruohotie (2000. The main

task is to develop a tool to help Virtual University students to identify their

motivational strategies and to improve their learning skills and strategies. The theory

of motivational strategies for learning developed by Pintrich and Ruohotie (2000) is

based on general social cognitive view of motivation, cognitions and metacognitions,

and self-regulated learning. The motivational constructs are interpreted rather as

social cognitive than as a need or a drive. The cognitive and metacognitive

components are seen from a general information processing perspective, not from a

structural and developmental view of cognition. (Pintrich & Mckeachie 2000.)

Motivated strategies of learning can be measured as an aptitude by self-ratings or as

an event observed by outsider rater (Winne & Perry 2000). Paul Pintrich (Pintrich,

Smith, Carcia, and McKeachie 1993) has developed Motivated Strategies for

Learning Questionnaire (MSLQ) to assess students’ motivation and cognition in the

classroom. MSLQ is based on students’ self-ratings. Pekka Ruohotie (1999) has

further developed the questionnaire in Finnish context of vocational teacher

education. In IQ-FORM research project the measurement of Motivational Strategies

for Learning Intelligent Questionnaire (MSLIQ) was adapted from the original MSLQ

by Pintrich (1993) and from the Finnish version adapted by Pekka Ruohotie (2000).

The first version of MSLIQ consisted of two parts: A) Learning Experiences and

Motivation and B) Cognitive and Metacognitive Learning Strategies.

Method The research project of motivational strategies is a part project of IQ-FORM research

project and it proceeds in the following phases: 1) pilot study – survey in order to test

the measurement of motivational strategies in learning, 2) validation and creation of a

MSLIQ tool for virtual university courses, 3) testing and retesting the MSLIQ tool in

real virtual university courses and with surveys. The research is thus action research,

where the aim is at the same time to develop and improve the virtual learning

environment to support more effective learning, and to gain new knowledge about

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motivational strategies students use in their learning. At the present paper the first

results of the pilot study are discussed. Pilot study

In the IQ-FORM research project a pilot study was taken in January 2001 to test the

measurements based on the theory of motivational strategies in learning (Pintrich &

Ruohotie 2000) and on Gardner’s multiple intelligence theory (Gardner 1983). The

data for pilot research was collected by a questionnaire from the undergraduate

students (N = 256) of five Finnish universities. In this study the aim is to test and

develop the measurement of motivational strategies for learning in order to create a

tool for IQ-FORM databank, which can be used by virtual university students and

their tutors. The research questions are: What are the motivational, metacognitive and

cognitive strategies for learning? What kind of differences can be found in

motivational, cognitive and metacognitive strategies for learning when compared the

groups by sex, age, main subject, or the tutorial guidance?

In order to develop the measurement of motivational strategies for learning the

confirmatory factor analysis procedures were run to validate the factorial structure of

MSLIQ. The influence of demographic data was analyzed by ANOVA.

Respondents were mostly young adult students (mean age 23,1; youngest 17 and

oldest 50), equally males (127, 50,2 %) and females (126, 49,8 %). They represented

five different majors (Humanities and Art, Social and Behavioral Sciences, Teacher

Education, Technology and Science, and Agriculture and Forest) from five different

universities (University of Helsinki, University of Joensuu, University of Tampere,

University of Oulu, and Helsinki University of Technology). Most students had

passed their matriculation exam and had began their studies in the University during

the years 1998 to 2000. Respondents were most commonly students of a first or a

second year, approximately 60 % of them had 20 to 60 study credits (for master

degree the demand is 160 study credits). Most of the students reported to have good

study motivation, and they were satisfied to their major. Most of the students (60 %)

told also that they had proceeded well in their studies. The demographic background

of students’ is presented in details in the Appendix 1.

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Validation of factorial structure of motivational scale

There were 26 items (a01 to a26) measuring learning experiences and motivation (part

A) and 40 items (b01 to b40) measuring the cognitive and metacognitive learning

strategies (part B). The scale runs from 1 (disagree strongly) to 5 (agree strongly).

Table 1 indicates the area of motivational strategies covered by questionnaire used in

the research project. In the table 1 is also presented the new model of measurement. First the motivational scale (Part A) was examined (items a01 to a26) and a forced

five-factor solution was used for theoretically acceptable results. The items for

separate factor analysis were selected based on theoretical analysis of measurement

(see table 1).

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Table 1. Theoretical and factorial structure of motivational strategies for learning

(adapted from Ruohotie & Nokelainen 2000, 163)

Target of measurement

Theoretical analysis of measurement instrument

Factorial structure A new model of the measurement

Value components • Intrinsic Goal Orientation • Task Value of Learning

Meaningfulness of Studies (fa3) Interest and Task value of Learning (fa3a) Utility of Studies (fa3b)

Expectancy components • Intrinsic Control Beliefs • Extrinsic Control Beliefs • Self-Efficacy • Expectancy for Success

Expectancy for Success (fa1) Self-Efficacy (fa4)

Part A Motivational scale

Affective components • Test Anxiety and Self-

Worth

Test Anxiety and Nervousness in a Test Situation (fa2)

Part A Motivational scale

Resource Management Strategies • Time and Study

Environment Management Strategy

• Effort Regulation Strategy

• Peer Learning Strategy • Help Seeking Strategy

Time Management strategy (fb1) Effort Regulation (fb2) Self-Regulation of Learning (fb2a) Persistence in Studies (fb2b) Help Seeking and Peer Learning strategy (fb4)

Part B Resource Management scale

Part B Cognitive scale

Metacognitive Strategies • Planning Activities • Monitoring Activities • Regulating Strategy Cognitive Strategies • Rehearsal Strategy • Elaboration Strategy • Organization Strategy • Critical Thinking Strategy

Rehearsal Strategy (fc1) Critical Thinking (fc2) Focus on Essential in Learning (fc3) Constructive Learning (fc4) Using Keywords (fc5) Application of Theory (fc6) Reflection on Learned (fc7)

Part C Cognitive scale

A forced four-factor solution and free solution (PCA) were used for comparison and

further examination of factorial structure. The five-factor solution explained total

variance 49,0 % (see table 2). Each of the five factors was tested with separate factor

analysis (method Maximum Likelihood with Varimax rotation), and the reliability of

the factors was tested with Cronbach’s alpha (see table 3).

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Table 2. A five-factor solution of the motivational scale.

Factors Variables

1 2 3 4 5

A01 ,489

A02 ,437 ,301 ,388

A03 ,314

A04 ,853

A05 ,795

A06 ,541 ,298

A07 ,449

A08

,313

A09

,626

A10 ,392 ,493

A11 ,663

A12 -,124 ,859

A13 -,404

A14 ,634

A15 ,601 ,357

A16 ,437 ,537

A17 ,559 ,307

A18 ,444 ,387

A19

,891

A20 ,695

A21 ,257 ,568

A22 ,912

A23 ,611

A24

,712

A26 ,554

Extraction Method: Maximum Likelihood. Rotation Method: Varimax with Kaiser Normalization. Rotation converged in 7 iterations.

Note: Values less than +/-.30 are suppressed.

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The expectation for success factor consisted of two dimensions: the will and the

expectation for good grades, and the belief in own ability to learn and success in

studies. Examination of factor showed that the variable A07 differed according to it’s

meaning from other variables (A07 “I want to obtain the best possible grades”) and it

was excluded from factor.

The anxiety and nervousness in test situation factor differentiated into two

dimensions: a) anxiousness due to a comparison of own performance with the peers'

performance, and b) nervousness during the test situation.

In original four-factor model the meaningfulness of studies consisted of intrinsic and

extrinsic motivation. According to the model the intrinsic and extrinsic motivation can

be described as one dimension, where a person is both intrinsically and extrinsically

motivated to study. The examination of factor showed that the meaningfulness of

studies factor could be divided into two different dimensions: a) Interest and Task

Value of Studies, and b) Utility Value of Studies.

The Self-Efficacy factor could be separated into two different dimensions: a) Self-

efficacy as a belief in own ability, and b) Self-efficacy as a belief in own effort. The

variables for the factor were selected to describe self-efficacy as a belief in own

effort. The factor will thus stress the meaning of intrinsic control beliefs.

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Table 3. Separate factor analysis of the five-factor solution for the motivational scale

Factor GFI for original

factor Alpha for original factor

GFI for modified one-factor model

Alpha for modified one-factor model

Expectation for Success (fa1) A05, A07, A11, A15, A20

37.6*** df 5

.78 5.10 n.s. df 2

.83

Anxiety and nervousness (fa3) A03, A08, A12, A14, A19

37.3*** df 5

.75 1.8 n.s df 2

.76

Meaningfulness of studies (Original) A01, A16, A17, A21, A22, A23, A26

368.9*** df 35

- - -

Interest and task value of studies A01, A16, A17, A21, A23, A26

25.6** df 9

.79 0.4 n.s. df 2

.73

Utility value of studies A04, A10, A13, A22

35.3 *** df 2

.77 - -

Self-Efficacy (effort) A02, A06, A09, A18, A24

81.4*** df 4

.62 62.6*** df 1

.64

Self-efficacy (ability) A02, A06, A18, A24

- - 11.2 ** df 2

.63

Extraction: Maximum Likelihood, Rotation: Varimax

Validation of factorial structure of cognitive and metacognitive scale

Second part of questionnaire (Part B) consisted of 40 items measuring the resource

management, and metacognitive and cognitive strategies of learning. First the

explorative factor analysis was run, and then the forced solution of a five-factor model

was examined. It consisted of five factors: Critical Thinking skills, Learning and

Note-taking skills, Effort regulation skills, Help Seeking Strategy and Time and Study

Environment Management Skills. The solution explained 37,4 % of variance (see

table 4). The result was compared with Kautto-Koivula study (1999) and Ruohotie

and Nokelainen (2000) analysis.

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Table 4. The five-factor solution of cognitive and metacognitive strategies in learning

Factor Variables

1 2 3 4 5

B01 ,604

B02 -,544

B03 ,404

B04 ,425

B05

,475

,655

B06 -,566

B07 ,533 ,314

B08 ,385

B09

-,493

B10 ,393

B11 ,529

B12 ,570

B13 ,378 ,351

B14

,659

B15 ,332 ,310

B16 ,615

B17 ,516

B18 ,503

B19 ,363 ,586

B20 ,672

Table continues.

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Table continues.

B21 ,501

B22 ,420 ,414

B23 ,586

B24 ,548 ,436

B25

B26 ,370

B27 -,540

B28 ,413

,119

B29 -,655

B30 ,497

B31 ,615 ,299

B32 ,542

B33 ,526

B34 ,427

B35 ,633

B36 ,617

B37 ,426

B38 ,807

B39 ,323

B40

Extraction Method: Maximum Likelihood. Rotation Method: Varimax with Kaiser Normalization. a Rotation converged in 8 iterations.

Note: Values less +/- .30 are suppressed.

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The further theoretical and confirmatory factor analysis of the structure of

measurement lead to the division of the measurement, which was divided into two

different parts: a) Resource Management Strategies (RMS) and b) Cognitive

Strategies in Learning (CSL). The items VB01, N02, B03, B05, B06, B09, B12, B13,

B14, B17, B18, B19, B25, B26, B27, B29, B36, B38, B39, and B40 were included

into RMS measurement (see new part B in table 1). The items B04, B07, B08, B10,

B11, B15, B16, B20, B21, B22, B23, B24, B28, B30, B31, B32, B33, B34, B35, and

B37 were included into CSL scale (see new part C in table 1).

The new factorial structure of RMS was tested first with an explorative factor analysis

(Maximum likelihood) and a free solution (PCA). The model of four factor solution

was selected and tested with forced Maximum Likelihood factor analysis. The result

of analysis supported the new model. Explanation of variance was 39.1 %. Each of

the four factors was tested with a separate factor analysis (method Maximum

Likelihood with Varimax rotation) and with reliability analysis (Cronbach's alpha)

(see table 5).

The new measurement of the CSL was first tested with forced a seven factor model

(Maximum Likelihood) (see table 6) and with a free solution (PCA). The model

explained 47,8 % of variance. The result showed that the model was approvable, but

needs to be modified and tested again. The rotated factor matrix is presented in the

table 6. The reliability of a seven factors’ theoretical model was tested with

Cronbachs’ alpha (see table 7).

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Table 5. Separate factor analysis of the four-factor solution for the resource

management scale

Factor GFI for one-

factor model Alpha for one-factor model

GFI for modified one-factor model

Alpha for modified one-factor model

Time Management (fb1) B01, B05, B12, B27

11.9 ** df 2

.71 -

-

Effort regulation (fb2) B02, B06, B13, B17, B18, B25, B26, B29, B36, B39

95.2 *** df 35

.77 - -

Self-Regulation of Learning (fb2a) B13, B18, B25, B26, B39

9.8 n.s. df 5

.63 - -

Persistence in Studies (fb2b) B02, B06, B17, B29, B36

6.6 n.s. df 5

.75 - -

Help Seeking and Peer Learning Strategy (fb4) B03, B09, B14, B19, B38, B40

38,2 *** df 9

.46 1.1 n.s df 2

.74

Method: Maximum Likelihood with Varimax rotation.

Time and study management factor included two components: a) conscientiousness in

keeping time, and b) effective use of time. There are different levels in time

management varying from monthly and weekly scheduling to the effective use of

current hour for studying. The factor did not describe the management of study

environment as in the original model.

In the Effort Regulation Strategy was distinguished two different aspects of

regulation: a) Self-Regulation in Learning and b) Persistence in Studies. Effort

regulation can be described as a student’s general self-management in terms of effort

and persistence. The further examination of two effort regulation dimensions showed,

that it was theoretically appropriate to divide effort regulation into two different

factors. The self-regulation in learning describes students’ ability to control and

monitor their own learning process and change the amount of effort demanded for

different study tasks. The persistence in learning is seen as a foresight and strength to

continue studies during the difficulties and / or dull study tasks. A persistent student

looks for the final goal of studies and can therefore stand for the inconvenience of a

current study period.

Peer Learning and Help-Seeking factor was validated as a student’s social ability to

ask help from peers in his/her study problems. This factor resembles Sternberg’s

(1985) notion of practical intelligence. A good student knows when he/she needs help

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and can also identify the person/s from whom to ask help. From the factor was

excluded variable B40 “I try to get feedback about my performance from my

teachers”, and so the factor emphasizes especially help seeking from peers.

Table 6. The seven-factor solution of cognitive learning strategies (20 items).

Factor 1 2 3 4 5 6 7

B04 ,413 ,196 ,233 ,134

B07 ,323 ,197 ,738 ,229 ,116 ,154

B08 ,550 ,367

B10 ,140 ,292 ,180 ,420

B11 ,593 ,308 ,120 ,355

B15 ,267 ,599

B16 ,400 ,131 ,530

B20 ,709 ,142 ,129 ,180

B21 ,468 ,297 ,300 ,191

B22 ,307 ,461 ,118 ,169 ,196 ,156 ,313

B23 ,152 ,183 ,126 ,295 ,507 ,193

B24 ,389 ,385 ,365 ,241 ,261

B28 ,340 ,296 ,251

B30 ,216 ,146 ,140 ,126 ,663

B31 ,570 ,167 ,211 ,279 ,105 -,116

B32 ,164 ,152 ,169 ,453 ,270 ,372

B33 ,201 ,142 ,699

B34 ,477 ,208 ,142 ,199 ,100

B35 ,468 ,154 ,110 ,383

B37 ,120 ,122 ,589 ,197 ,139

Extraction Method: Maximum Likelihood. Rotation Method: Varimax with Kaiser Normalization. a Rotation converged in 13 iterations.

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Table 7. The Seven-factor solution for cognitive strategies (20 items)

Factor Items Alpha

Rehearsal Strategy B08, B37 .42

Critical Thinking Strategy B07, B16, B33 .65

Focus on the Essential

Strategy

B11, B30 .53

Constructive Thinking

Strategy

B15, B22 .60

Use of Keywords Strategy B23, B28, B32 .60

Application of Theory

Strategy

B21, B24, B34, B35 .71

Reflection on Learned

Things Strategy

B04, B10, B20, B31 .64 (B10 excluded)

.60 (B10 included)

Rehearsal strategy of learning is outlined as a basic cognitive strategy with

elaboration, and organizational strategies of learning. Each of these strategies also has

a basic and a complex version, depending on the nature of a learning task (Pintrich &

McKeachie 2000, 41.) Here the rehearsal strategy describes more a complex than a

basic strategy. For the next phase in the research project the items belonging to this

factor were reformed in order to stress the meaning of more deep rehearsal learning

strategy.

Critical thinking strategy is described as a students’ ability to solve problems, make

critical evaluations, and comparisons. There is done plenty of research on this area,

and also in the new virtual learning environment and distance education area (eg.

Bullen 1998). The factor was found reliable (alpha .65).

The Focus on Essential strategy describes how students’ concentrate and find out the

essential and central ideas in their learning material. A good student is not only taking

notes of all the material she / he studies, but also organizes learning material to more

important and less important areas.

Constructive Thinking strategy means that a student is able to combine a new

knowledge with his / her previous knowledge and construct the meaning of studied

subjects.

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Use of Keywords strategy resembles close the previous focus on essential strategy. A

student makes notes of the central concepts and ideas, classifies them. These

keywords can be used during rehearsal period of the study process, and thus the

rehearsal becomes more complex and leads to more deep understanding in learning.

Application of Theory strategy can described as a students’ application of learned

theories, new things, into different everyday situations, or as a comparison of theories.

The transfer of learning resembles this factor.

Reflection on Learned strategy is used, when a student concentrates to think over the

learned things and makes questions, creates analogies, or explains the things he / she

has learned. This strategy can be described also as an elaboration strategy.

The effect of tutorial guidance to students’ motivational and

cognitive strategies in learning

The main task of the research project (IQ-FORM) is to develop a tool for students,

and their teachers or tutors, in order to improve students’ learning strategies. The tool

will work like an intelligent electronic helper or tutor for a student, and help him/her

to become more aware of his/her motivational strategies in learning. The aim is, that a

student can with the help of IQ-FORM-tool develop his/her own study planning and

management skills.

For the evidence of the meaningfulness of the new factorial structures of MSLIQ the

ANOVA procedures were run to examine the connections between the three different

scales (MS, RMS, CSL) of MSLIQ and received tutorial guidance. The students who

had received tutorial help during there studies were selected from data (N = 182).

Students were classified into three groups according to the amount of tutorial help

they had received during their studies. Students who had got plenty tutorial help

(N=12, 3 males and 9 females) were only few, but for a more detailed analysis they

were kept as a one group. Students with some tutorial help (N = 69, 46 % males and

54 % females) were classified as a group and so were also students with a minimum

tutorial help (N = 101, 53 % males and 47 % females). Students with more tutorial

help came from universities of Helsinki and Joensuu and students with less tutorial

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help were from universities of Oulu and Tampere. There were found no differences in

receiving tutorial help according to the age.

Table 8. Group: Tutorial help. Mean Scores, standard deviations (in parentheses) and F-values with significance on factors of motivational strategies. Factor Groups: Amount of a tutorial help during the studies

Plenty

N = 12

Some

N = 69

Minimum

N = 101

All

N = 182

F (sig)

Expectation of Success

4.00 (0.36)

3.76 (0.54)

3.49 (0.75)

3.62 (0.67)

5.5 **

Anxiety and Nervousness in a test situation

2.23 (0.88)

2.37 (0.83)

2.43 (0.89)

2.39 (0.86)

0.33 n.s.

Interest and Task Value of Studies

3.88 (0.87)

3.85 (0.54)

3.61 (0.71)

3.72 (0.67)

2.94 p<.055

Utility Value of Studies

4.17 (0.47)

4.15 (0.59)

3.93 (0.71)

3.72 (0.67)

2.53 p>.082

Self-Efficacy (effort)

3.71 (0.46)

3.87 (0.58)

3.96 (0.56)

3.91 (0.56)

1.31 n.s.

Students who had got more tutorial guidance reported that their belief in success in

their studies is higher compared with students with less or no tutorial guidance.

Students with more tutorial guidance had also higher interest for their studies and they

were more motivated for utility values in studies. These latter differences are not

statistically significant. Females, who had received tutorial help, were more motivated

of the interest and task value of the studies than males (F = 7.04, p<.01). Females and

males had no differences in motivational strategies in no-tutorial guidance group.

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Table 9. Group: Tutorial help. Mean Scores, standard deviations (in parentheses) and

F-values with significance on factors of resource management strategies.

Factor Groups: Amount of a tutorial help during the studies

Plenty

N = 12

Some

N = 69

Minimum

N = 101

All

N = 182

F (sig)

Time Management Strategy

3.00 (0.89)

3.12 (0.83)

2.63 (0.76)

2.84 (0.83)

8.04 ***

Effort Regulation

3.27 (0.62)

3.32 (0.52)

3.15 (0.69)

3.22 (0.63)

1.58 n.s.

Persistence in Studies

3.54 (0.58)

3.42 (0.73)

3.14 (0.77)

3.27 (0.76)

3.64 *

Peer Learning and Help Seeking Strategy

3.08 (0.89)

3.50 (0.61)

3.36 (0.81)

3.40 (0.75)

1.84 n.s.

Students with more tutorial help were more effective in their time management

strategies and were also more persistent in their studies compared with the students

with less tutorial guidance. There were no significant differences between males and

females in resource management strategies for learning, and the groups with tutorial

guidance and no-tutorial guidance did not also differ.

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Table 10. Group: Tutorial help. Mean Scores, standard deviations (in parentheses)

and F-values with significance on factors of cognitive strategies.

Factor Groups: Amount of a tutorial help during the studies

Plenty

N = 12

Some

N = 69

Minimum

N = 101

All

N = 182

F (sig)

Rehearsal Strategy

3.04 (0.84)

3.20 (0.70)

3.01 (0.75)

3.08 (0.74)

1.44 n.s.

Critical Thinking Strategy

3.14 (0.85)

3.03 (0.77)

2.78 (0.79)

2.90 (0.80)

2.59 p<.08

Focus on the Essential Strategy

3.79 (0.75)

3.93 (0.58)

3.53 (0.77)

3.70 (0.73)

6.82 ***

Constructive Thinking Strategy

4.46 (0.62)

4.08 (0.66)

3.90 (0.66)

4.00 (0.67)

4.69 **

Use of Keywords Strategy

3.47 (1.08)

3.63 (0.71)

3.20 (0.85)

3.38 (0.85)

5.86 **

Application of Theory Strategy

3.67 (0.73)

3.58 (0.61)

3.35 (0.73)

3.46 (0.70)

2.81 p<.06

Reflection on Learned Things Strategy

3.08 (0.83)

3.07 (0.66)

2.82 (0.71)

2.93 (0.70)

2.9 p<.06

Students with more tutorial guidance used more effective cognitive learning strategies

compared with students with less tutorial guidance. Females used more focusing on

essential (F = 6.32, p< .01), constructive thinking in learning (F = 8.70, p<.01) and

keywords (F = 29.4, p<.001) while studying than males. There were no significant

differences between females and males in no-tutorial guidance group.

Conclusions and suggestions for the future research

Confirmatory factor analysis revealed the semantic meanings of items and helped to

validate factorial structure of motivational strategies in learning. Validation procedure

leaded to the conclusion that the division of a latter part of MSLIG was necessary.

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The part B (cognitive and metacognitive strategies in learning) was divided into two

different parts; resource management strategies measurement and cognitive strategies

measurement. The new tool for MSLIQ consisted of three different parts: A)

Motivational Strategies scale (MSS), B) Resource Management Strategies scale

(RMS), and C) Cognitive Learning Strategies scale (CSL). Some of the items were

reformulated and thus there is need for a new survey to test the MSLIQ. The new

model of measurement is presented in the table 1.

The tutorial guidance seemed to have positive effects on students’ motivational

strategies in learning and helping them to develop more effective cognitive learning

strategies. There where found significant differences between females and males, and

it seems to be possible to suppose that especially women seem to be able to profit

tutorial help they receive during their studies. The quality of tutorial guidance may

cause the difference between sexes and further research is needed to explore the

nature and quality of tutorial in universities.

There is still a need to develop the measurement for motivational strategies in

learning. The next step in research project is to test validated MSLIQ using it in real

virtual university courses to find out the benefits and limitations of the tool. The

research will thus continue in testing the created MSLIQ-tool in the virtual learning

environment of Finnish Virtual University. Also the measurement tool needs to be

tested again with a new survey research.

References

Gardner, H. (1993). Multiple intelligences. The theory in Practice. New York: Basic Books.

Gardner, H. and Hatch, T. 1989. Multiple intelligences go to school. Educational

Researcher, 18 (8).

IQ-Research group (2001a). A test based on Gardners’ multiple intelligence theory called: "What kind

of person am I? Department of education, University of Helsinki

IQ-Research group (2001b). Three test sets adapted from motivation tests developed by P. Pintrich and

P. Ruohotie, A test about the students view on herself as a student, a test of learning

strategies and a test about cognitive functions. Department of Education, University of

Helsinki

21

Niemi, H. (2000a, September 23). Identification of learning profiles and motivation strategies in virtual

university learning spaces. Paper presented at the European Conference on Educational

Research, 20-23 September 2000, University of Edinburgh, Scotland, U.K. Session under

the title Issues in Open and Virtual Learning, September 23rd.

Niemi, H. (in preparation). Empowering learners in Virtual University through identification of

learning profiles and motivation strategies. A paper for a book on e-Learning (in

preparation, edited by Ruohotie & Beaistro), May 2001

Pintrich, P. & Ruohotie, P. (eds.) (2000). Conative constructs and self-regulated learning. RCVE:

Hämeenlinna, Finland.

Pintrich, P. R. & McKeachie, W. J. 2000. A framework for conceptualizing student motivation and

self-regulated learning in the college classroom. In Paul Pintrich & Pekka Ruohotie (Ed.),

Conative constructs and self-regulated learning. Hämeenlinna: Research Centre for Vocational

Education. 31-50.

Pintrich, P. R. & Ruohotie, P. (ed.) 2000. Conative constructs and self-regulated learning.

Hämeenlinna: Research Centre for Vocational Education.

Pintrich, P. R., Smith, D., Garcia, T. & McKeachie, W. J. (1993) Reliability and Predictive Validity of

The Motivated Strategies for Learning Questionnaire (MSLQ). Educational and

Psychological Measurement, 53, 801-813.

Ruohotie, P. 1999. Growth prerequisties in organizations. In P. Ruohotie, H. Tirri, P. Nokelainen & T.

Silander (Eds.) Modern modelling of professional growth. Research Centre for Vocational

Education. University of Tampere.

Ruohotie, P. & Nokelainen, P. 2000. Modern modelling of student motivation and self-regulated

learning. In Paul Pintrich & Pekka Ruohotie (Ed.), Conative constructs and self-regulated learning.

Hämeenlinna: Research Centre for Vocational Education. 141-193.

Winne, P. H. & Perry, N. E. Measuring self-regulated learning. In Monique Boekaerts, Paul P. Pintrich and Moshe Zeidner (ed.) Handbook of self-regulation. San Diego: Academic Press. Contact: Senior Researcher Anne Nevgi Department of Education, University of Helsinki 00014 University of Helsinki Tel. 358 9 191 28008 Fax: 358 9 191 28073 e-mail: anne.nevgi@helsinki.fi IQ-FORM-research project: http://www.edu.helsinki.fi/iqform/

22

Appendix 1 The demographic background of students’ is presented in the following table 1. Table 1. Students’ demographic background, academic Success, study motivation, and received tutorial help. Frequencies (%). Variable Scale Value

Sex

Males Females Missing

127 (50,2) 126 (49,8)

3 (1,2) Age

Minimum Maximum Mean SD Missing

19 50

23.1 4.6

6 University

Helsinki Joensuu Tampere Oulu Technical University Missing

41 (16.1) 64 (25.2) 46 (18.1) 78 (30.7) 25 (9.8)

2 (0.8)

Demographic background

Major Humanities and Art Social and Behavioral Sciences Teacher Education Technology and Science Agriculture and Forest Some other Missing

6 (2.4) 39 (15.3) 46 (18.0)

117 (45.9) 35 (13.7) 12 (4.7)

1 (0.4) Academic Success

Year of Matriculation

1969-1995 1996-1998 1999-2000 Missing

62 (24.9) 134 (53.8) 53 (21.3)

7 (2.7) Matriculation

Grades Native Language (N) - mean - SD Mathematics (N) - mean - SD Humanities and Science (N) - mean - SD Second National Language (N) - mean - SD First Foreign Language (N) - mean - SD

(249) 3.98 1.17

(225) 3.67 1.33

(246) 4.07 1.26

(249) 3.72 1.41

(248) 3.31 1.34

Table continues on the next page.

23

Table continues.

Entrance Year into University

1977-1995 1996-1998 1999-2000 Missing

18 (7.2) 119 (47.4) 114 (45.4)

5 (2.0) Study credits Less than 20 credits

21 to 60 credits 61 to 100 credits More than 100 credits Missing

51 (20.0) 106 (41.6) 52 (20.4) 46 (18.0)

1 (0.4)

Study Success Very well Quite well Medium Quite poor Very poor

48 (18.8) 114 (44.5) 72 (28.1) 21 (8.2)

1 (0.4) Satisfaction with the Choice of Major

Very sure Quite sure Medium Quite unsure Very unsure

90 (35.2) 114 (44.5) 33 (12.9) 14 (5.5)

5 (2.0) Satisfaction with the present Major

Very satisfied Unsure I would like to change if possible

158 (62.2) 85 (33.5) 11 (4.3)

Study Motivation

Present Study Motivation

Very good Quite good Medium Quite poor Very poor

34 (13.3) 126 (49.2) 71 (27.7) 23 (9.0)

2 (0.8) Tutorial help during the studies

Tutorial help from teachers, tutors, or other study counselors

Very much Much Medium Quite few Not at all Missing

0 12 (4.7)

69 (27.1) 101 (39.6) 73 (28.6)

1 (0.4)