Dirk Tempelaar

Maastricht University, Quantitative Economics, Department Member

Followers

136

Following

Co-authors

Public Views

Researcher of dispositional learning analytics

less

Interests

Uploads

Papers by Dirk Tempelaar

Cultural Diversity in Academic Motivation: Universality and Model Complexity

Cross-Cultural Education Studies, 2025

This contribution centres on two interconnected conjectures. The first posits that motivational—a... more This contribution centres on two interconnected conjectures. The first posits that motivational—and the way we model what influences motivation— can be significantly enhanced by integrating the concept of growth orientation. This integration enables to connect growth mindset frameworks and motivational theories through straightforward antecedent-consequence models. The second conjecture is that simpler models tend to vary less and are more stable across different groups compared to more complex models. An example brings these two conjectures together by analysing cultural differences in academic motivation. It compares three models using data from international students studying mathematics and statistics: (1) a comprehensive growth orientation model incorporating both global and specific factors, estimated using Bifactor Exploratory Structural Equation Modelling (B-ESEM); (2) a simplified version of this model with growth orientation as the sole antecedent factor; and (3) a Structural Equation Model (SEM) using specific factors as antecedents. In the illustrative example, the degree of cultural diversity in motivational levels is found to be relatively small, comparable in magnitude to gender differences. However, more complex antecedent-consequence models can easily lead to the conclusion that significant diversity exists between cultural groups. Our findings challenge common assumptions about the cultural specificity of academic motivation models and highlight a promising yet often overlooked factor for building robust explanations of learning motivation: students’ growth orientation.

Distance Education And Problem-Based Learning

Educational Innovation in Economics and Business Administration, 1995

Download

Social Presence, Web Videoconferencing and Learning in Virtual Teams

Industry and higher education, Aug 1, 2009

For guidance on citations see FAQs.

Download

The development of students' subject attitudes when taking a statistics course

Abstract In this empirical study, we investigate two research questions related to students&a... more Abstract In this empirical study, we investigate two research questions related to students&amp;#x27; attitudes toward statistics in a sample of 3500 first year university students. The first question is inspired by a large body of research that concludes that learning attitudes tend to decline while learning for the subject. Using the SATS attitudes instrument that distinguishes six attitudes factors, Affect, Cognitive Competence, Value, Difficulty, Interest, and Effort, we indeed confirm this downward trend, with the exception of Value. But the downward ...

A structural equation model analyzing the relationship of student achievement motivations and personality factors in a range of academic subject-matter areas

Contemporary Educational Psychology, 2007

The question of subject-speciWcity of achievement motivations is important, both for educational ... more The question of subject-speciWcity of achievement motivations is important, both for educational psychology, as well as for educational policy. This study contributes to the investigation of the heterogeneity in achievement motivations in the context of the expectancy-value model. Whereas existing research deals with middle and high school students and their motivations for a range of broad domains, this article focuses on university students (n D 264) and subject domains that are more congruent. We adopt an aVect-extended version of the expectancy-value model. Using structural equation methods, we are able to decompose achievement motivations in generic and subject-speciWc components.

Download

Antecedents of learning behaviour in a blended learning environment

How Dispositional Learning Analytics Helps Understanding the Worked-Example Principle

International Association for Development of the Information Society, Oct 1, 2017

This empirical study aims to demonstrate how Dispositional Learning Analytics can contribute in t... more This empirical study aims to demonstrate how Dispositional Learning Analytics can contribute in the investigation of the effectiveness of didactical scenarios in authentic settings, where previous research has mostly been laboratory based. Using a showcase based on learning processes of 1080 students in a blended introductory quantitative course, we analyse the use of worked examples by students. Our method is to combine demographic and trace data from technology enhanced systems with self-reports of several contemporary social-cognitive theories. We find that the same maladaptive learning orientations that play a role in worked examples learning theories as to explain the effectiveness of worked examples do predict the use of worked examples: this time in the role of individual learning dispositions.

Download

Individual differences in the preference for worked examples: Lessons from an application of dispositional learning analytics

Applied Cognitive Psychology, Mar 27, 2020

Worked-examples have been established as an effective instructional format in problem-solving pra... more Worked-examples have been established as an effective instructional format in problem-solving practices. However, less is known about variations in the use of worked examples across individuals at different stages in their learning process in student-centred learning contexts. This study investigates different profiles of students' learning behaviours based on clustering learning dispositions, prior knowledge, and the choice of feedback strategies in a naturalistic setting. The study was conducted on 1,072 students over an 8-week long introductory mathematics course in a blended instructional format. While practising exercises in a digital learning environment, students can opt for tutored problem solving, untutored problem solving, or call worked examples. The results indicated six distinct profiles of learners regarding their feedback preferences in different learning phases. Finally, we investigated antecedents and consequences of these profiles and investigated the adequacy of used feedback strategies concerning 'help-abuse'. This research indicates that the use of instructional scaffolds as worked-examples or hints and the efficiency of that use differs from student to student, making the attempt to find patterns at an overall level a hazardous endeavour.

Download

Het blenden van probleemgestuurd groepsonderwijs en flexibel, geïndividualiseerd digitaal onderwijs

Learning analytics to understand cultural impacts on technology enhanced learning

Cognition and Exploratory Learning in Digital Age, Nov 1, 2016

In this empirical study, we investigate the role of national cultural dimensions as distal antece... more In this empirical study, we investigate the role of national cultural dimensions as distal antecedents of the use intensity of e-tutorials, which constitute the digital component within a blended learning course. Profiting from the context of a dispositional learning analytics application, we investigate cognitive processing strategies and metacognitive regulation strategies, motivation and engagement variables, and learning emotions as proximal antecedents of tool use and tool performance. We find that cultural diversity explains a substantial part of the variation in learning dispositions and tool use. The design of personalized learning paths will, therefore, profit from including national cultural dimensions as a relevant design factor.

Download

Creating Conditions for Collaborative Learning

Springer eBooks, Jul 20, 2005

Research has shed light on different perspectives which are relevant to making collaborative lear... more Research has shed light on different perspectives which are relevant to making collaborative learning successful (Slavin, 1996). Based on that research, we are able to develop quantitative models that explain the success of a collaborative learning group in terms of underlying motivational, cognitive, and interactional processes (Dolmans et al., 1998). Having measured the extent to which students in a problem-based learning group motivate each other, form a cohesive group, participate actively, or in contrast, sponge or withdraw, these models contribute to our understanding of why some groups are productive, and others are not. Models of this kind are, however, of limited practical use: they are useful for explaining ex post why specific groups have less than average productivity, but cannot explain ex ante what conditions (except for choices of instructional technology) are needed to increase the perspectives of success in collaborative learning groups. In order to develop a model with predictive power, this study investigated group processes in a problem-based learning environment in relation to the types of group interaction taking place (based on Bales’ Interaction Process Analysis, IPA) and personal characteristics of students and tutors. The aim of the research is to develop a model that explains the success of collaborative learning groups, via

What learning analytics based prediction models tell us about feedback preferences of students

The Quarterly Review of Distance Education, 2016

The Open University's repository of research publications and other research outputs What learnin... more

Download

A multi-modal study into students’ timing and learning regulation: time is ticking

Interactive Technology and Smart Education, Jul 1, 2018

The Open University's repository of research publications and other research outputs A multi-moda... more

Download

Effectiveness of a Voluntary Postsecondary Remediation Program in Mathematics

This chapter evaluates a postsecondary remediation program in mathematics, aiming to ease the tra... more This chapter evaluates a postsecondary remediation program in mathematics, aiming to ease the transition from high school to university and to improve the success rates in the first year of bachelor studies. The remediation program consists of voluntary bridging education in the format of an online summer course. We investigate five cohorts of in total 4500 students of Maastricht University School of Business and Economics, with 578 participants in the remedial education program. Effect analysis suggests a strong treatment effect of ...

Student Learning Preferences in a Blended Learning Environment: Investigating the Relationship Between Tool Use and Learning Approaches

Springer eBooks, 2011

Building on research into the demands on students&amp;amp;amp;amp;amp;amp;#x27; self-regulate... more Building on research into the demands on students&amp;amp;amp;amp;amp;amp;#x27; self-regulated learning when learning about conceptually rich domains with computer-based learning environments (CBLEs)(Azevedo, Current perspectives on cognition, learning, and instruction, 2008; Lajoie and Azevedo, Handbook of educational psychology, 2006), our study focuses on the research question how students self-regulate their learning in a blended learning environment. In the teaching of introductory statistics to first-year students in economics ...

Stability and Sensitivity of Learning Analytics based Prediction Models

For guidance on citations see FAQs.

Download

Investigating learning strategies in a dispositional learning analytics context

This study aims to contribute to recent developments in empirical studies on students' learni... more This study aims to contribute to recent developments in empirical studies on students' learning strategies, whereby the use of trace data is combined with self-report data to distinguish profiles of learning strategy use [3--5]. We do so in the context of an application of dispositional learning analytics in a large introductory course mathematics and statistics, based on blended learning. Building on our previous work which showed marked differences in how students used worked examples as a learning strategy [7, 11], this study compares different profiles of learning strategies with learning approaches, learning outcomes, and learning dispositions. One of our key findings is that deep learners were less dependent on worked examples as a resource for learning, and that students who only sporadically used worked examples achieved higher test scores.

How Cultural and Learning Style Differences Impact Students’ Learning Preferences in Blended Learning

IGI Global eBooks, Aug 13, 2012

In teaching introductory statistics to first year students, the Maastricht University uses a blen... more In teaching introductory statistics to first year students, the Maastricht University uses a blended learning environment that allows them to attune available learning tools to personal preferences and needs, in order to address large diversity in students. That diversity is a direct consequence of a heterogeneous inflow of primarily international students, transferring from different secondary school systems with large differences in prior knowledge, and transferring from very different cultural backgrounds. In this empirical contribution, the authors focus on the role an adaptive online tutorial as component of the blend can play in bridging the consequences of a broad range of differences such as prior mastery of the subject, cultural background, and learning approaches. They do so by investigating the relationships between the intensity of the use of the e-tutorial and students' characteristics related to nationality, cultural background, learning styles, goal-setting behavior, achievement motivations, self-concept constructs, and subject attitudes.

Download

Towards Actionable Learning Analytics Using Dispositions

IEEE Transactions on Learning Technologies, 2017

Studies in the field of learning analytics (LA) have shown students' demographics and learning ma... more Studies in the field of learning analytics (LA) have shown students' demographics and learning management system (LMS) data to be effective identifiers of "at risk" performance. However, insights generated by these predictive models may not be suitable for pedagogically informed interventions due to the inability to explain why students display these behavioral patterns. Therefore, this study aims at providing explanations of students' behaviors on LMS by incorporating dispositional dimensions (e.g., self-regulation and emotions) into conventional learning analytics models. Using a combination of demographic, trace, and self-reported data of eight contemporary social-cognitive theories of education from 1,069 students in a blended introductory quantitative course, we demonstrate the potential of dispositional characteristics of students, such as procrastination and boredom. Our results highlight the need to move beyond simple engagement metrics, whereby dispositional learning analytics provide an actionable bridge between learning analytics and educational intervention.

Download

Web-spijkeren I & II

Dirk Tempelaar

Uploads

Papers by Dirk Tempelaar

Log In