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.
The Emerging Field Group initiative is intended to support researchers active in innovative and exciting fields. An Emerging Field Group (EFG) consists of a small group of internationally active researchers working in the field of learning and instruction active within a new, emerging field of research. EARLI offers these researchers the opportunity to work together during a short but intense period of time to explore the possibilities in their shared field of interest.
EFGs are intended for exploratory, innovative and risk-taking approaches. Being part of an Emerging Field Group allows for its participants to focus on experimental and new fields of research, with an emphasis on exploration and process rather than output and product.
SIG 27 Biennial Conference: New Deadline 5th February
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)
NEW Submission Deadline: 5th February
Find Abstract Submission here
Conference Website: http://konferencjaet.neurodevice.pl
Conference Contact: firstname.lastname@example.org or tel: +48 22 662 15 30
SIG 27 – Motivation & Emotion: https://www.earli.org/node/50
The theme of the JURE Conference 2018 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.
JURE Conference 2018 Dates:
Conference: 02 – 06 July 2018
Submission NEW Deadline: 31.12.2017
Registration Open: 01.02.2018
Early Bird Deadline: 03.05.2018
JURE Conference 2018 Contact:
Conference Contact: email@example.com
Twitter: https://twitter.com/2018JURE #2018
JURE Website: https://www.earli.org/jure
JURE 2018 Flyer can be found 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.
Call for Papers: Mobile Technology, Learning, and Achievement: A Critical Perspective on the Role of Mobile Technology in Education
The purpose of this special issue of Contemporary Educational Psychology (CEP) is to rigorously investigate the affordances and challenges of mobile and wearable technologies as platforms for both measuring and inducing processes that foster achievement and learning. Such tools hold great promise as a way to collect online, measures of learner functioning, from non-intrusive biometrics through direct-contact interaction data. They also can serve as educational tools, prompting learners as well as affecting the learning environment. At the same time, mobile technology presents new challenges and new hindrances to effective education, particularly when such technology is used without grounding in learning and learning theory.
– Matthew L. Bernacki, University of Nevada, Las Vegas
– Jeffrey A. Greene, University of North Carolina at Chapel Hill
– Helen Crompton, Old Dominion University
Deadline: May 15, 2018
Format: 1-2 page summary
Submit summaries to Matt Bernacki (firstname.lastname@example.org
Find more research papers here.
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)
Application Deadline for Summerschool: 15th January 2018
ICM: 15th – 17th August 2018 (Wednesday – Friday)
NEW Submission Deadline: 15.12.2017
Conference Website: http://conferences.au.dk/icm-2018/
SIG 8 – Motivation & Emotion: http://motivation-emotion.eu
Submission Instructions can be found here
The Concept of Learning Outcomes Often Follows Behaviourist Tradtion
Learning outcomes as a concept has encountered a revival since the beginning of the Bologna process in 1999. The concept itself has a longer history with its roots in the behaviourist tradition of the 1960s. The goal of this review is to study how the historical roots of learning outcomes are noted in current research articles since the launch of the Bologna process and whether the concept of learning outcomes is used critically or uncritically. The review of 90 articles shows that the behaviourist tradition is still evident in the 21st century research with 29% of the articles directly and 11% indirectly referring uncritically to the respective publications or to the behaviourist epistemology.
Citation: Murtonen, M., Gruber, H., & Lehtinen, E. (2017). The return of behaviourist epistemology: A review of learning outcomes studies. Educational Research Review, 22(Supplement C), 114-128.
Find the full article here: https://doi.org/10.1016/j.edurev.2017.08.001
Find more interesting articles here.
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.
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.
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.
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).
At the conference of “Bildung und Begabung” [Education & Giftedness] 31 May 2016 with the title “Perspektive Begabung: Diversität als Chance” [Future of Giftedness: Diversity as an Opportunity] Thomas Martens delivered a keynote entitled “Motivation and Educational Perspectives of Gifted Children”.
While one child follows his interests and develops remarkable skills herein, the other child seems rather lackluster and disinterested. Researcher have long been agreed that motivation is a driving factor when giftedness is translated into performance. As different as young people are so different are their motivation profiles. Family, friends, and teachers – they all influence the development of motivation. This can be promoted by empathetic caregivers or be attenuated in critical phases of life. How can we, in the face of these different conditions, support children and young people developing motivation and regulating them properly? How can school or other learning environments handle these motivation processes? What help can be offered?
A podcast of this talk is online (german only):
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!!!)