Thomas Martens is Professor for Educational Psychology at the Medical School Hamburg. He is contract teacher at the Goethe University of Frankfurt am Main in educational psychology and education. Thomas Martens was senior researcher and test coordinator in the Technology-Based Assessment (TBA) Project at the German Institute for International Educational Research (DIPF) in Frankfurt. Now he is an associated scientist at the DIPF. He holds degrees in psychology and higher education, and a Ph.D in psychology. He served as chair for the “International Conference on Motivation 2012” and led the International Scientific Board for the “International Conference on Motivation 2014”. Thomas Martens coordinated the Special Interest Group “Motivation and Emotions” within the European Association for Learning and Instruction (EARLI) and is Editor-in-Chief of Frontline Learning Research. He is a project manager in the joint project “Sensor Measures of Motivation for Adaptive Learning (SensoMot) (SensoMot)“. Thomas Martens has a strong background in testing and evaluation, e-learning, as well as in motivational regulation.
Call for Papers – Frontline Learning Research – Special Issue
New measurements of learning:
Emerging chances and challenges of process measures.
Deadline: April 15th, 2018
Over the recent years, research within EARLI increasingly focuses on studying learning as a process (how and why does the learning take place?) rather than just the outcomes of learning. As a consequence, process measures, so far used mainly in fundamental research (e.g., eye tracking, EEG), are increasingly being applied to educational science. Process measures make it possible to measure and visualize learning processes as they happen. This application requires the development of novel methodological approaches. The current special issue aims at critically discussing these methods with respect to their explanatory power for researching learning. In research practice, these measures offer researchers many opportunities, but they also raise many challenges. These include combining process measures of different levels of granularity synchronizing measures, capturing the sequential nature of learning processes and defining reasonable epochs for analyses. Often, these challenges go by unnoticed as there is rarely any room to discuss them in traditional empirical study papers. Due to this lack of exchange, researchers often re-invent the wheel.
The contributions to this special issue should include studies on learning that apply these new measurements and put their findings up for discussion. The aim of this special issue is that all contributions reflect on the strengths and limitations of their measures and provide a statement on how informative their data can be for researching learning. The discussants will address these statements and relate the papers to the current state of learning research.
This special issue is based on the initiative of EARLI SIG 14 and EARLI SIG 27. However, all interested researchers are invited to contribute to this special issue. All articles will be thoroughly reviewed according to standards of Frontline Learning Research, an official EARLI journal.
If you are interested in contributing to this call, please send a 300-word abstract to Ellen Kok (firstname.lastname@example.org) before December 20th, 2017.
The guest editors,
Dr. Christian Harteis
Dr. Halszka Jarodzka
Dr. Ellen Kok
Conditioning factors of test‑taking engagement in PIAAC: an exploratory IRT modelling approach considering person and item characteristics
A potential problem of low-stakes large-scale assessments such as the Programme for the International Assessment of Adult Competencies (PIAAC) is low test-taking engagement. The present study pursued two goals in order to better understand conditioning factors of test-taking disengagement: First, a model-based
approach was used to investigate whether item indicators of disengagement consti-tute a continuous latent person variable by domain. Second, the effects of person and item characteristics were jointly tested using explanatory item response models.
Analyses were based on the Canadian sample of Round 1 of the PIAAC, with N= 26,683 participants completing test items in the domains of literacy, numeracy, and problem solving. Binary item disengagement indicators were created by means of item response time thresholds.
The results showed that disengagement indicators define a latent dimension by domain. Disengagement increased with lower educational attainment, lower
cognitive skills, and when the test language was not the participant’s native language. Gender did not exert any effect on disengagement, while age had a positive effect for problem solving only. An item’s location in the second of two assessment modules was positively related to disengagement, as was item difficulty. The latter effect was negatively moderated by cognitive skill, suggesting that poor test-takers are especially likely to disengage with more difficult items.
The negative effect of cognitive skill, the positive effect of item difficulty, and their negative interaction effect support the assumption that disengagement is
the outcome of individual expectations about success (informed disengagement).
Goldhammer, F., Martens, T. & Luedtke, O. (2017). Conditioning factors of test-taking engagement in PIAAC: an exploratory IRT modelling approach considering person and item characteristics. Large-scale Assessments in Education, 5, 18. DOI: 10.1186/s40536-017-0051-9 [html, pdf]
Please find other publications here.
The European Association for Research on Learning and Instruction (EARLI) is an international networking organisation for junior and senior researchers in education. EARLI has 27 Special Interest Groups representing researchers who study one or more parts and/or aspects of the field of Learning and Instruction.
This new and free Handbook of Learning Analytics covers a broad sprectrum of topics including Emotion (from Sidney D’Mello) and Self-Regulated Learning (from Philip Winne).
This book is edited by Charles Lang, George Siemens, Alyssa Wise & Dragan Gašević
The full book can be downloaded for free here (CC BY 4.0)
Citation: Lang, C., Siemens, G., Wise, A., & Gašević, D. (Eds.). (2017). The Handbook of Learning Analytics. Society for Learning Analytics Research.
Find the table of content here.
The next SIG 27 Biennial Conference will be held at University of Warsaw, Institute of Applied Linguistics, Poland. The Conference will jointly organized with the 6th Polish Eye Tracking Conference. But of course all other Online Measures covered in SIG 27 are also welcome.
Conference Dates: 15th – 17th June 2018 (Friday morning to Sunday afternoon)
Submission Deadline: to be announced
Conference Website: http://konferencjaet.neurodevice.pl
Conference Contact: email@example.com or tel: +48 22 662 15 30,
SIG 27 – Motivation & Emotion: https://www.earli.org/node/50
The next International Conference on Motivation 2018 will be held at Aarhus University, Danish School of Education, Denmark. The chair will be Niels Bonderup Dohn
Summer school: 12th – 14th August 2018 (Sunday – Tuesday)
ICM: 15th – 17th August 2018 (Wednesday – Friday)
Submission Deadline: 10.12.2017
Conference Website: http://conferences.au.dk/icm-2018/
SIG 8 – Motivation & Emotion: http://motivation-emotion.eu
Submission Instructions can be found here
Buildung on the central contributions of Julius Kuhl like the PSI Theory leading researchers including Charles S. Carver and Richard M. Ryan reflect the implications for their own work.
This book is edited by Nicola Baumann, Miguel Kazén, Markus Quirin & Sander L. Koole
Citation: Baumann, N., Kazén, M., Quirin, M., & Koole, S. L. (Eds.). (2018). Why People Do the Things They Do. Göttingen: Hogrefe.
Please find the table of content here.
The next conference of the JUnior REsearcher (JURE) of the European Association for Learning and Instruction (EARLI) will be held at the University of Antwerp, Belgium.
The theme of the JURE 2018 conference is “Learning and instruction with an impact – scaling up the skill, will and thrill of learning”. The conference presentations, workshops and keynotes will showcase the newest findings about the cognitive, motivational and emotional aspects of learning and highlight the practical implications for practice and policy.
Dates: 02 – 06 July 2018
Submission Deadline: 12.12.2017
Registration Open: 01.02.2018
Early Bird Deadline: 03.05.2018
Conference Website: https://www.uantwerpen.be/en/conferences/jure-2018/
Conference Contact: firstname.lastname@example.org
Twitter: https://twitter.com/2018JURE #2018
JURE Website: https://www.earli.org/jure
JURE 2018 Flyer can be found here
Thomas Martens conducted a workshop on 30 June 2016 at the TU Dresden with the title “Fostering Learning at University: the Heterogeneity of Motivational Processes”. This workshop showed different ways of learning motivation and how the individual learning processes of students can be promoted.
As theoretical basis served the Integrated Model of Learning and Action (IMLA) which divides the typical processes of learning in three main phases (motivation, intention and volition phase) and defines the relationship to the findings in neuro science from Julius Kuhl (2000).
This chapter discusses transitions towards learning at university from a perspective of regulation processes. The Integrated Model of Learning and Action is used to identity different patterns of motivational regulation amongst first-year students at university by using mixed distribution models. Five subpopulations of motivational regulation could be identified: students with self-determined, pragmatic, strategic, negative and anxious learning motivation. Findings about these patterns can be used to design didactic measures to support students’ learning processes.
Please find a preview of this chapter here.
Please cite this chapter as: Martens, T. & Metzger C. (in press). Different Transitions of Learning at University: Exploring the Heterogeneity of Motivational Processes. Erscheint in E. Kyndt, V. Donche, K. Trigwell & S. Lindblom-Ylänne (Eds.), Higher Education Transitions: Theory and Research. EARLI Book Series “New Perspecitves on Learning and Instruction”. London: Routledge.
New research projekt started: Sensor Measures of Motivation for Adaptive Learning (SensoMot)
Motivation is one major factor for facilitating deep learning processes. The goal of the research project „SensoMot“ is to predict critical motivational conditions using sensor measures. By deriving adaptive mechanisms, the learning process can subsequently be tailored to the motivational needs of the learner (project description).
This article examines conditions for a successful motivation for education and training: Why can many teenagers and young adults easily motivate themselves for schools and education, while other show serious motivational difficulties? On the base of identified motivational processes measures are suggested that educational institutions can provide.
(available in German language only – sorry!!!)