This document summarizes a study that analyzed how student motivation and strategy use impacted outcomes in a business school course with digital learning components. The study collected data from 189 students over 12 weeks, including participation data, surveys on motivation and strategy use, and interviews. It found that student motivation decreased from the beginning to middle of the course in areas like intrinsic goal orientation and task value. Strategy use remained mostly consistent. A cluster analysis grouped students into three profiles based on motivation and strategy use levels, with the highest scoring cluster associated with better course outcomes. The study provides insights into how blended learning designs can impact student motivation and performance.

1. The Impact of Motivation
and Strategy Use on Course
Outcome in Digital
Learning Environment- A
case Analysis of a Business
School Course
Shadi Esnaashari, Lesley Gardner, Michael Rehm,
January, 2020

2. Overview
• Introduction
• Literature review
• Theoretical frame work
• Research methodology
• Data Analysis

3. Growing demand for
education

4. Slide title
Google Image

5. Class participation
under researched
http://www.uu.se/asp/about-active-student-participation/goodexamples
https://www.facultyfocus.com/articles/teaching-and-learning/10-benefits-of-getting-students-to-participate-in-classroom-discussions/

6. Participation and engagement

7. Top Hat

8. Research Gaps
• How does the motivation of students change
over the course and to what extent does
student motivation affect their course
outcome?”

9. Literature review- Prediction
Techniques Studies
Decision tree (Cortez & Silva, 2008), (Bresfelean, 2007), (Kabra &
Bichkar, 2011), (Romero, Ventura, Espejo, & Hervás,
2008)
Neural network (Sheel, Vrooman, Renner, & Dawsey, 2001),
(Lykourentzou et al., 2009), (Pinninghoff Junemann,
Salcedo Lagos, & Contreras Arriagada, 2007), (Cortez &
Silva, 2008), (Fausett & Elwasif, 1994), (Romero et al.,
2008)
Regression
techniques
(Kotsiantis & Pintelas, 2005), (Talavera & Gaudioso,
2004), (Hämäläinen & Vinni, 2006), Lykourentzou,
Giannoukos, Mpardis, Nikolopoulos, & Loumos, 2009)
Bayesian network (Ayers & Junker, 2006), (Hämäläinen & Vinni, 2006)

10. Theoretical framework
We have to remind ourselves
• “learning analytics is about learning”.
(Gašević, Dawson, and Siemens, 2015)

11. Activity theory Leontiev
extended by Engeström (2001)

12. Self-regulated learning
 Learners construct their knowledge
Learners use tools
to operate on raw materials
to construct a product
 Learners are agents
 Learners are agents which means that they decide
what to study and when to stop their studies. Students
evaluate themselves during the process of learning.

13. Method
• Context of the study
• Participants
• Ethics
• Data collection
• Data analysis

14. STUDY DESIGN
• Students in a Business School at a New
Zealand university.
• The courses lasted for 12 weeks.
• Data is available for 189 students.
• TechSmith platform.
• Tests at the end of each video module.
• Tournaments through Top Hat.
• Survey questionnaire to understand the
perception of students regarding using
different tools.
• The Motivated Strategies for Learning
Questionnaire (MSLQ)

15. Research process

16. Data collection(Quantitative and
qualitative)
• In-class participation data (Top Hat)
• Out of class participation data (Canvas)
• The Motivated Strategies for Learning
Questionnaire (MSLQ)
• Students interviews

17. Motivation
Value
Affective
Expectancy
Intrinsic goal
orientation
Extrinsic goal
orientation
Task Value
Control Beliefs
Self-efficacy
Test Anxiety

18. Strategy
Rehearsal
Cognitive and Meta cognitive strategy
Resource management strategies
Elaboration
Organization
Critical Thinking
Metacognitive self-
regulation
Time and Study
Environment
Effort regulation
Peer learning
Help Seeking

19. Students’ perception

20. Instrum
ents
Benefits
Videos Students exercised control over their own learning, and reviewed resources at their own
and pace.
They had captions.
They did not have to commute to and from the University
They did not have to carry hard copy books.
Students found Learning was enjoyable and they were encouraged to attend classes
Lecturer directly communicated with students
Quizzes Quizzes were used as a revision tool.
Students could encoding the main concepts of the course
Students could reflect on their learning.
Supporting the lecturer
Top hat Students’ answers were anonymized.
Students appreciated revisiting concepts.
Piazza Students did not trust using Piazza.
Review
sessions
The environment was engaging and fun.
Opportunity for students to reflect on their learning.
Help to understand most important content

21. Factors Description
Sense of
community loss
Having no classes, students feel they don’t have any community to interact
with.
Students could not forge friendships.
Mental health
issues
Staying at home all the time impacted students’ wellbeing.
Less engagement
in the blended
environment
Helped students to procrastinate
Attending the physical classroom was more helpful- students would write
more notes and did not postpone things.
Procrastination Students needed to have a minimum self-control in order to be able to control
their learning.

22. Time 1 Time 2 Time 3
Mean S.D Mean S.D Mean S.D
Motivation
Value
Components
Intrinsic goal orientation 4.71 .85 4.55 .89 4.52 1.00
Extrinsic goal orientation 5.40 1.08 5.11 1.10 5.10 1.11
Task Value 5.32 1.00 4.28 .81 5.10 1.03
Value Components 15.43 2.25 13.95 2.19 14.71 2.59
Expectancy
Components
Control Beliefs 5.16 .86 5.14 .81 5.05 .916
Self-efficacy for Learning and
Performance
4.96 .88 4.89 .91 4.84 .99
Expectancy Components 10.13 1.49 10.03 1.49 9.88 1.69
Affective
Components
Test Anxiety 4.64 1.13 4.50 1.14 4.60 1.22
Affective Components
4.65 1.14 4.51 1.14 4.60 1.22
Motivation 30.22 3.70 28.49 3.61 29.20 4.37
Strategyuse
Cognitive and
Metacognitive
Strategies
Rehearsal 4.43 1.02 4.67 1.03 4.77 1.05
Elaboration 4.58 .83 4.60 .94 4.71 .95
Organization 4.88 .84 4.72 .90 4.82 .93
Critical Thinking 3.84 1.03 3.91 .96 3.91 1.15
Metacognitive self-regulation
4.30 .69 4.38 .71 4.42 .74
Cognitive and Metacognitive Strategies
21.93 3.41 22.29 3.47 22.64 3.72
Resource
Management
Strategies
Time and Study Environment
4.82 .78 4.70 .85 4.60 .87
Effort regulation 4.85 1.06 4.72 1.04 3.72 .84
Peer learning 3.42 1.34 3.33 1.40 3.59 1.42
Help Seeking 3.24 1.21 3.20 1.24 3.33 1.30
Resource Management Strategies
16.25 2.78 15.95 2.86 15.25 2.87

23. Time 1 Time 2
Time 2
Mean
Std.
Deviation
Mean Std.
Deviation
Mean Std.
Deviation
Motivation 30.22 3.70 28.49 3.61 29.20 4.37
Strategy 38.18 5.36 38.23 5.48 37.89 5.75

24. Time 1 Time 2 Time 3
Mean SD Mean SD Mean SD
Value Components 15.43 2.25 13.95 2.19 14.71 2.59
Expectancy Components 10.13 1.49 10.03 1.49 9.88 1.69
Affective Components 4.65 1.14 4.51 1.14 4.60 1.22
Cognitive and Metacognitive
Strategies
21.93 3.41 22.29 3.47 22.64 3.72
Resource Management
Strategies
16.25 2.78 15.95 2.86 15.25 2.87

25. MSLQ analysisTime 1 Time 2 Time 3
Mean SD Mean SD Mean SD
Intrinsic goal orientation 4.71 .85 4.55 .89 4.52 1.00
Extrinsic goal orientation 5.40 1.08 5.11 1.10 5.10 1.11
Task Value 5.32 1.00 4.28 .81 5.10 1.03
Control Beliefs 5.16 .86 5.14 .81 5.05 .916
Self-efficacy for Learning and
Performance
4.96 .88 4.89 .91 4.84 .99
Test Anxiety 4.64 1.13 4.50 1.14 4.60 1.22
Rehearsal 4.43 1.02 4.67 1.03 4.77 1.05
Elaboration 4.58 .83 4.60 .94 4.71 .95
Organization 4.88 .84 4.72 .90 4.82 .93
Critical Thinking 3.84 1.03 3.91 .96 3.91 1.15
Metacognitive self-regulation 4.30 .69 4.38 .71 4.42 .74
Time and Study Environment 4.82 .78 4.70 .85 4.60 .87
Effort regulation 4.85 1.06 4.72 1.04 3.72 .84
Peer learning 3.42 1.34 3.33 1.40 3.59 1.42
Help Seeking 3.24 1.21 3.20 1.24 3.33 1.30

26. Cluster Analysis
1 2 3
Value Components1 11.00 20.17 11.50
Expectancy Components1 9.13 12.00 11.63
Affective Components1 4.40 6.40 4.60
Cognitive and Metacognitive Strategies1 16.80 20.43 19.50
Resource Management Strategies1 13.50 17.29 11.92
Value Components2 8.83 17.92 9.92
Expectancy Components2 9.13 12.88 12.38
Affective Components2 3.80 6.00 2.00
Cognitive and Metacognitive Strategies2 16.57 29.35 13.85
Resource Management Strategies2 11.46 20.46 6.88
Value Components3 6.00 19.25 10.33
Expectancy Components3 8.63 12.25 12.00
Affective Components3 3.80 5.60 1.20
Cognitive and Metacognitive Strategies3 16.83 29.00 18.38
Resource Management Strategies3 10.07 20.78 8.93
Final Score 13.66 47.82 43.39

27. • Thank you for listening.
• Any questions and comments:
S.Esnaashari@Auckland.ac.nz