E-learning with multiple-try-feedback: can hints foster students’ achievement during the semester?

E-learning opportunities have become an increasingly important component of university education. Various laboratory studies have shown that e-learning environments can meaningfully enhance learning by incorporating various interventions and design choices (e.g., providing feedback and scaffolds). However, many computer-based interventions have not yet been applied in authentic university courses, raising questions about whether and how the provision of certain forms of feedback works and scales in an applied context. In this paper, we addressed this research gap. Specifically, we investigated whether including an elaborative component (hints) in multiple-try feedback increases student learning in e-learning exercises in an undergraduate statistics course. In one exercise, after completing a statistical problem, one group received feedback that conveyed knowledge about the correct response, while the other group additionally received elaborative feedback in the form of hints. We conducted an experimental comparison of these two types of feedback with third-semester sociology students in the tutorial component of an introductory statistics course. The results show that additional feedback helps students perform better during the session and on a delayed test one week later. Implications for further research and the application of such e-learning environments in university settings are discussed

Instructional Support for Enhancing Students’ Information Problem Solving Ability

Brand-Gruwel, S., & Gerjets, P. (Eds.). (2008). Instructional Support for Enhancing Students’ Information Problem Solving Ability [Special issue]. Computers in Human Behavior, 24(3).This special issue discusses European research on instructional support to foster students’ ability to solve information-based problems. In this introduction, the concept of information problem solving (IPS) and research in this field of interest will be placed in the broader perspective, which is called information behavior. The focus of this special issue is an educational one and the papers all go into a specific kind of instructional support. The main research questions, findings and conclusions of the six contributions will be outlined. It is concluded that the most important directions for future research deal with how instructional support for different aspect of the process, like for instance how to regulated the process, best can be designed in order to make the instruction adaptive and fit to the learners needs

In the eyes of the beholder: How experts and novices interpret dynamic stimuli

Jarodzka, H., Scheiter, K., Gerjets, P., & Van Gog, T. (2010). In the eyes of the beholder: How experts and novices interpret dynamic stimuli. Learning and Instruction, 20, 146-154. doi:10.1016/j.learninstruc.2009.02.019Tasks with a complex, dynamic visual component require not only the acquisition of conceptual/procedural but also of perceptual/attentional skills. This study examined expertise differences in perceiving and interpreting complex, dynamic visual stimuli on a performance and on a process level, including perceptual and conceptual strategies. Performance, eye movement, and verbal report data were obtained from seven experts and 14 novices. Results show that experts compared to novices attend more to relevant aspects of the stimulus, use more heterogeneous task approaches, and use knowledge-based shortcuts. Implications for instructional design for the acquisition of perceptual skills are discussed

Attention guidance during example study via the model’s eye movements.

Van Gog, T., Jarodzka, H., Scheiter, K., Gerjets, P., & Paas, F. (2009). Attention guidance during example study via the model’s eye movements. Computers in Human Behavior, 25, 785-791.Research has shown that guiding students’ attention guides their thought, and that attention can be communicated via eye movements. Therefore, this study investigates whether such a procedure can further enhance the effectiveness of examples in which a solution procedure is demonstrated to students by a (expert) model. Students’ attention was guided by showing them not only the model’s problem-solving actions on the computer screen, but also the model’s eye movements while doing so. Interestingly, results show that combined with a verbal description of the thought process, this form of attention guidance had detrimental effects on learning. Consequences for further research on attention guidance and instructional design are discussed

How to understand & write literature with AI? Potentiale und Risiken von KI-Tools für Literarisches Lesen und Schreiben

Künstliche Intelligenz dringt zunehmend in künstlerisch-kreative Handlungsfelder vor, die bislang als genuin menschliche Tätigkeiten angesehen wurden. Damit rücken auch Facetten der digitalen Rezeption und Produktion literarischer Gegenstände in den Blick, die bisher im literaturdidaktischen Diskurs kaum eine Rolle gespielt haben: Mit nichtmenschlichen Akteuren zu literarischen Texten interagieren oder literarisch mit Hilfe einer Maschine schreiben, verändert die Erfordernisse und Bedingungen literarischer Texterschließung und Kommunikation außerhalb und innerhalb von schulischen Kontexten. Da es im Umgang mit Literatur jedoch seit jeher nicht nur auf das „Verstehen“ eines Ausgangstextes, sondern ebenso auf seine emotionale, körperliche und somit individuelle bzw. erfahrungsbezogene Aneignung ankommt, wirft der Einbezug von KI-Tools in den Literaturunterricht weitreichende Fragen auf. Der Beitrag fragt daher explorativ, wie sich die Anschlusskommunikation zu literarischen Texten mit Unterstützung von sprachbasierten KI- Tools hier einordnen lässt und welche Transformationen bisheriger schreib- und literaturdidaktischer Normen und Praktiken damit ggf. einhergehen werden.   Abstract (english): How to unterstand & write literature with AI? Potentials and risks of KI tools for literary reading and creative writing Artificial intelligence is increasingly making inroads into artistic and creative fields of action that were previously regarded as a genuinely human purview. As a result, facets of the digital reception and production of literary objects that have hardly played a role in didactic discourse to date are now coming into focus: Interactions with non-human actors when discussing literary texts, or even writing literary texts with the help of a machine that can imitate virtually all voices and patterns prevalent in world literature changes the requirements of literary text development and communication outside and within school contexts. However, since dealing with literature has always depended not only on the „understanding“ of a source text, but also on its emotional, physical and thus individual or experiential acquisition, the inclusion of AI tools in literature lessons raises far-reaching questions, not only from a media education and media ethics perspective. Hence, the article explores how follow-up communications to literary texts with the support of language-based AI tools can be categorised and which transformations of norms and practices of writing and literary didactics may be associated with this development

The two-component model of memory development, and its potential implications for educational settings

We recently introduced a two-component model of the mechanisms underlying age differences in memory functioning across the lifespan. According to this model, memory performance is based on associative and strategic components. The associative component is relatively mature by middle childhood, whereas the strategic component shows a maturational lag and continues to develop until young adulthood. Focusing on work from our own lab, we review studies from the domains of episodic and working memory informed by this model, and discuss their potential implications for educational settings. The episodic memory studies uncover the latent potential of the associative component in childhood by documenting children's ability to greatly improve their memory performance following mnemonic instruction and training. The studies on working memory also point to an immature strategic component in children whose operation is enhanced under supportive conditions. Educational settings may aim at fostering the interplay between associative and strategic components. We explore possible routes towards this goal by linking our findings to recent trends in research on instructional design

Conveying clinical reasoning based on visual observation via eye-movement modelling examples

Jarodzka, H., Balslev, T., Holmqvist, K., Nyström, M., Scheiter, K., Gerjets, P., & Eika, B. (2012). Conveying clinical reasoning based on visual observation via eye-movement modelling examples. Instructional Science, 40(5), 813-827. doi:10.1007/s11251-012-9218-5Complex perceptual tasks, like clinical reasoning based on visual observations of patients, require not only conceptual knowledge about diagnostic classes but also the skills to visually search for symptoms and interpret these observations. However, medical education so far has focused very little on how visual observation skills can be efficiently conveyed to novices. The current study applied a novel instructional method to teach these skills by showing the learners how an expert model visually searches and interprets symptoms (i.e., eye-movement modelling examples; EMMEs). Case videos of patients were verbally explained by a model (control condition) and presented to students. In the experimental conditions, the participants received a recording of the model’s eye movements superimposed on the case videos. The eye movements were displayed by either highlighting the features the model focused on with a circle (the circle condition) or by blurring the features the model did not focus on (the spotlight condition). Compared to the other two conditions, results show that a spotlight on the case videos better guides the students’ attention towards the relevant features. Moreover, when testing the students’ clinical reasoning skills with videos of new patient cases without any guidance participants studying EMMEs with a spotlight showed improved their visual search and enhanced interpretation performance of the symptoms in contrast to participants in either the circle or the control condition. These findings show that a spotlight EMME can successfully convey clinical reasoning based on visual observations