Presentations from the fifth biennial SIG22 Neuroscience and Education conference
Monday 4th – Wednesday 6th June 2018
London, United Kingdom
SIG 22 brings together researchers from the fields of educational science, cognitive psychology, developmental psychology, genetics, and neuroscience as well as interdisciplinary people with training in each of these fields, all of which investigate human learning and development. Taking interdisciplinarity as a basic principle, the SIG conceives the relation between educational research and neuroscience as a two-way street with rich bi-directional and reciprocal interactions between educational research and (cognitive) neuroscience.
10 Presentations in total:
The 18th Biennial European Conference for Research on Learning and Instruction (EARLI 2019) will be hosted by the RWTH Aachen University from August 12th until August 16th 2019.
The theme of the conference is Thinking Tomorrow’s Education: Learning from the past, in the present, and for the future. In times of constant changes, the future is a moving target – difficult to predict and prepare for. Yet, education is doing just that. At the 18th Biennial EARLI Conference and the accompanying 23rd Conference of the Junior Researchers of EARLI, researchers in learning and instruction from all over the world come together to discuss current research findings. In order to think tomorrow’s education and education research, it is crucial to relate new findings to what we already know and to elaborate how this will help foster sustainable learning processes and navigating what is yet to come.
Submissions open: 1. September 2018
Submissions Deadline: 30. October 2018
Early Bird Deadline: 3. April 2019
Call for Submissions: PDF
All information about the upcoming EARLI 2019 conference can be found at https://www.earli.org/earli2019.
First of all, one might wonder if motivated learning is necessary at all. Is is not possible to learn without motivation? At least as far as short-term learning success is concerned, this question must be answered positively: it is possible to successfully learn without motivation. However, the empirical results from our “Zeitlast” (workload) studies also show that such a learning outcome without motivation is usually accompanied by a greater perceived effort and a higher objective time requirement. It may also be assumed that the acquired knowledge content is less accessible – in particular, that the transfer to new situations is disrupted resulting in some inertia of the knowledge thus acquired.
Conversely, it can be inferred that motivated learning requires less personal effort, is more time-effective and the resulting knowledge is more universally applicable.
These advantages of motivated learning are directly related to the fact that intrinsic motivation is linked to the self-system “extension memory” already described in the blogpost 1 “Descartes’ Error“. The right hemispheric extension memory accompanies and enables the internalization processes necessary to perform a learning task with intrinsic motivation.
Here, the extension memory has a threefold function:
- It allows feeling the fit between learning tasks and the learner and thus creating a first internalization of the learning task. Subsequently, an ascription of responsibility for the learning task can be developed.
- The extension memory also accompanies the experience of self-efficacy. In particular, whether a particular learning method or learning strategy really suits you.
- In the actual performing of the learning action, the extension memory will assess whether I continue to feel comfortable with the concrete learning processes.
The activation of the extension memory in the learning process is thus the prerequisite for a holistic association of the self with all phases of the learning process. A large correspondence between the self and the learning regulation will trigger the effects of an intrinsic motivation:
- Learning is easy and time flies by (flow experience).
- Through a high degree of associations with the self-system many methods can be associated that can be used flexibly during the learning process.
- A close connection with the self-system also enables a better self-motivation, which allows a constructive handling of setbacks and, if necessary, guarantees a longer study of the subject matter.
- Finally, strong associations of the acquired knowledge with the self-system result in a more flexible retrieval of the knowledge content in different situations and thus promotes a high retention performance.
The next blog post will explain how a learning environment can be designed in such a way that the highest possible intrinsic motivation for learning can emerge (motivated design).
This work is licensed uner Attribution-NonCommercial-ShareAlike 4.0 International
Call for Papers: “Capturing the Dynamics of Emotion and Emotion Regulation in Daily Life With Ambulatory Assessment”
A Special Issue of the European Journal of Psychological Assessmentedited by Peter Koval, Elise Kalokerinos, Philippe Verduyn, and Samuel Greiff
How people experience and regulate their emotions in daily life lies at the heart of their psychological functioning. Recognising this, affective scientists are increasingly adopt- ing ambulatory assessment (AA) methods to study the dynamics of emotional experience and regulation in daily life, a trajectory that has been accelerated by the proliferation of smartphones and other mobile/wearable devices. For the purpose of this special issue, we define AA as any naturalistic method used to capture experience, behaviour, or physiology in daily life, including (but not limited to) experience sampling, ecological momentary assessment, diary methods, the Electronically Activated Recorder (EAR), passive sensing, continuous physiology monitoring, etc.
Despite growing interest in the use of AA methods in affective science, many challenges remain, including the development of valid and reliable tools for measuring emo- tions and emotion regulation in daily life; statistical models that capture (bi-directional) relations between emotions and emotion regulation; and methods and models for cap- turing how emotions and emotion regulation dynamically interact with other psychological, physiological, and behavioural processes, and with contextual factors in daily life. The current special issue aims to highlight the important challenges facing researchers who apply AA methods to the study of emotion and emotion regulation in daily life, and to propose some possible solutions.
Letters of interest (LOI) for this special issue are due on September 1, 2018. Please click here for more information.
Let’s do a simple thought experiment: when I think of violence, am I a criminal? When I think of giving presents to someone else, am I a benefactor?
Even in this simple thought experiment, it becomes clear that conscious thinking can always focus on just one point – just as speaking does. Does this one focus defines human being? Hardly likely.
What constitutes humanity much more is the sum of the experiences of a human being. This wealth of experiences could therefore be considered as being human.
The exciting question is now how we draw on this wealth of experience. Certainly, we can consciously remember a single event in our past. However, does that help us to recognize who we are?
There is one system that is able to assess the vast majority of personal experiences at once. Personality psychologist Julius Kuhl calls this system “extension memory”. This system can assess a person’s wealth of experience in a parallel and holistic way and gives a feeling as a result of this assessment.
This self-system or so-called extension memory becomes especially important when it comes to assessing and evaluating social interaction in a matter of seconds. For example, when I meet a person I did not know before, after a very short time I know how to judge that person.
Maybe this first assessment is not very accurate. But at least it gives an indication of how I should deal with this person in the future. Thus, the extension memory is capable of retrieving all associations with a new person within a very short period of time and of pooling those associations in a feeling for that person. Therefore, if everything goes well, within a few moments I know if I can trust this person. Or if I’d rather avoid this new person.
The extension memory is also responsible for a whole series of processes, such as the intrinsic motivation for learning, which we just demonstrated in the current research project Sensomot – read this in the next blog post “motivated learning“.
So we can say with certainty that Descartes was wrong. This sentence might be much more accurate:
“Sentio, ergo sum.” (I feel, therefore I am)
This work is licensed uner Attribution-NonCommercial-ShareAlike 4.0 International
The next EARLI SIG 6-7 Meeting “Instructional Design and Technology for 21st Century Learning: Challenges, Solutions und Future Directions” will be held at the DIE (German Institute for Adult Education) August 22th – 24th in Bonn.
EARLI SIG 6-7 Meeting: 22th – 24th August 2018
Conference Website: https://earli.org/SIG6-7
In the 21st century, learning and instruction are becoming increasingly learner-centered. This is reflected by a rise in adaptive and personalized instruction, an emphasis on learner-initiated generative learning strategies, and an increased focus on self-regulated learning skills and learner motivation. Challenges in 21st century learning include the development of data and information literacy, issues of privacy and data security, and effects of globalization, digitalization, and migration on formal, non-formal, and informal learning. During the meeting, state of the art research within the field of learning and instruction will be presented, with special attention to technological advancements within this field. How are the trends and challenges listed above reflected in research on (technology-enhanced) learning and instruction? What are the challenges that we are facing, and what are possible solutions? What future directions are relevant in research on (technology-enhanced) instructional design?
The Promises and Pitfalls of Self-report Data for Motivation and Strategy Use: The Congruence of Theory, Self-reported Data Collection, Analysis and Reported Results
Deadline: August 31th, 2018
While self-report measures are ubiquitous in the educational research literature, the benefits of self-report are often maligned. Rather than discarding or ignoring data generated from self-report measures of cognitive processing and motivation, research is needed to determine when and if self-report measures can contribute to our collective understanding of theory surrounding these constructs. This special issue will examine how self-report accurately reflects the constructs of cognitive and motivational processing, how these measures influence analytic choices, and how these measures ultimately influence our interpretations of study findings.
Without understanding the ripple effects of the choice of self-report on other aspects of the research process, the reported findings of these studies and their consequences on theories and practices remain in question. Providing empirical and theoretical support for the use of self-report (or not) can help clarify some of these pressing issues. Methodologies to investigate self-report will cover both qualitative and quantitative examinations of these issues. Potential contributions to this special issue should include studies in the areas of learning strategy use and motivation/emotion for learning. Empirical and theoretical contributions are welcomed. Studies should address two of three following questions:
- In what ways do self-report instruments reflect the conceptualizations of the constructs suggested in theory related to motivation or strategy use?
- How does the use of self-report constrain the analytical choices made with that self-report data?
- How do the interpretations of self-report data influence interpretations of study findings?
Papers will be synthesized by three leading international scholars who are recognized as international experts (Phil Winne, Peggy Van Meter, and Reinhard Pekrun) in the measurement of their respective constructs. This special issue is based on the initiative of the Network for Learning Strategies Group based out of the University of Antwerp. 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 400-500-word abstract to Luke Fryer (email@example.com) by August 31th, 2018.
The guest editors,
Dr. Dan Dinsmore
Dr. Luke K. Fryer
Call for Papers – SIG 22 Special Issue for Mind, Brain and Education
Deadline: September 15thth, 2018
This special issue invites all SIG22 members and/or conference participants to submit an article to contribute to the SIG22 Conference 2018 special issue. If you have a paper in progress from the work you presented at the conference, or any other work related to both (cognitive) neuroscience and education, this special issue will guarantee a wide readership and thereby reach a lot of relevant people. Given the quality and diversity of the posters and talks at the conference, the guest editors are looking forward to many submissions to make this a very exciting and interesting issue of Mind, Brain and Education!
If you are interested in contributing to this call, please send an abstract to Saabine Peter (firstname.lastname@example.org) before September 15th 2018.
(Guest) associate editors of the special issue are
- Sabine Peters (Leiden University),
- Nienke van Atteveldt (VU University Amsterdam),
- Bert de Smedt (Leuven University) and
- Iroise Dumontheil (Birkbeck, University of London).
– Please follow the regular article guidelines for authors:
- Please note that MBE does not publish purely educational submissions, or purely neuroscience submissions. MBE articles are those that integrate across fields with experiments or reviews/commentaries.
SIG 27 Biennial Conference: Earli Bird Registration ends End of May
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)
Earli Bird Registration:until End of May 2018
Find the Congress Programme here
Conference Website: http://konferencjaet.neurodevice.pl
Conference Contact: email@example.com or tel: +48 22 662 15 30
SIG 27 – Online measures of learning processes’ https://www.earli.org/node/50
The Emerging Field Group initiative is intended to support researchers active in innovative and exciting fields. EARLI Emerging Field Groups (EFG) consist 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.
Following a lengthy evaluation procedure, four applications have been granted the EARLI Emerging Field Group funding for 2018 – 2020.
Portable Brain Technologies in Educational Neuroscience Research
led by Nienke van Atteveldt, VU Amsterdam, the Netherlands
The Potential of Biophysiology for Understanding Learning and Teaching Experiences
led by Lars-Erik Malmberg, Oxford University, United Kingdom
Unifying Cognitive Load and Self-Regulated Learning Research: Monitoring and Regulation of Effort (MRE)
led by Anique de Bruin, Maastricht University, the Netherlands
EarlyWritePro: Developing Methods for Understanding Early Writing through Analysis of Process Dysfluencies
led by Mark Torrance, Nottingham Trent University, United Kingdom
The first two EARLI emerging field groups nominees show that triangulation and combination of new data sources like portable EEG and other physiological data promise new insights into learning and regulation processes. It can be expected that these emerging fields will gain strength within in the scientific community for the next years.
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.
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!!!)