Deutsches Institut für Internationale Pädagogische Forschung (DIPF)
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Learning to solve graph tasks is one of the key prerequisites of acquiring domain-specific knowledge in most study domains. Analyses of graph understanding often use eye-tracking and focus on analyzing how much time students spend gazing at particular areas of a graph—Areas of Interest (AOIs). To gain a deeper insight into students’ task-solving process, we argue that the gaze shifts between students’ fixations on different AOIs (so-termed transitions) also need to be included in holistic analyses of graph understanding that consider the importance of transitions for the task-solving process. Thus, we introduced Epistemic Network Analysis (ENA) as a novel approach to analyze eye-tracking data of 23 university students who solved eight multiple-choice graph tasks in physics and economics. ENA is a method for quantifying, visualizing, and interpreting network data allowing a weighted analysis of the gaze patterns of both correct and incorrect graph task solvers considering the interrelations between fixations and transitions. After an analysis of the differences in the number of fixations and the number of single transitions between correct and incorrect solvers, we conducted an ENA for each task. We demonstrate that an isolated analysis of fixations and transitions provides only a limited insight into graph solving behavior. In contrast, ENA identifies differences between the gaze patterns of students who solved the graph tasks correctly and incorrectly across the multiple graph tasks. For instance, incorrect solvers shifted their gaze from the graph to the x-axis and from the question to the graph comparatively more often than correct solvers. The results indicate that incorrect solvers often have problems transferring textual information into graphical information and rely more on partly irrelevant parts of a graph. Finally, we discuss how the findings can be used to design experimental studies and for innovative instructional procedures in higher education
This study examined age‐related differences in the effectiveness of two generative learning strategies (GLSs). Twenty‐five children aged 9–11 and 25 university students aged 17–29 performed a facts learning task in which they had to generate either a prediction or an example before seeing the correct result. We found a significant Age × Learning Strategy interaction, with children remembering more facts after generating predictions rather than examples, whereas both strategies were similarly effective in adults. Pupillary data indicated that predictions stimulated surprise, whereas the effectiveness of example‐based learning correlated with children’s analogical reasoning abilities. These findings suggest that there are different cognitive prerequisites for different GLSs, which results in varying degrees of strategy effectiveness by age.
Objective: Although meaning making and specifically autobiographical reasoning are expected to relate to well‐being, findings tend to be mixed. Attempts at meaning making do not always lead to meaning made. We aimed to disentangle these complex relationships and also explore the role of level of education.
Method: Ninety participants (mean age 36.73 years, SD = 7.27; 74.4% women, 25.6% men) who had experienced the loss of a parent through death, going missing, or Alzheimer's disease narrated this loss, a sad, a turning point, and a self‐defining memory, and completed questionnaires assessing depression, trauma symptoms, and protracted grief. Three aspects of autobiographical reasoning (quantity, valence, and change‐relatedness of self‐event connections) were related to meaning made (sophistication of meaning making) and symptom level.
Results: Years of education correlated both with positive implications of autobiographical reasoning and with meaning made. The quantity, positivity, and change‐relatedness of attempts at meaning making (self‐event connections) predicted accomplished meaning made, and positivity alone predicted less prolonged grief.
Conclusions: Adapting the life story after a loss such that change of the self is acknowledged and positive change can be constructed helps finding meaning and lowering protracted grief. These changes in narrative identity are supported by more years of education.
In this explorative study, we investigate how sequences of behaviour are related to success or failure in complex problem‐solving (CPS). To this end, we analysed log data from two different tasks of the problem‐solving assessment of the Programme for International Student Assessment 2012 study (n = 30,098 students). We first coded every interaction of students as (initial or repeated) exploration, (initial or repeated) goal‐directed behaviour, or resetting the task. We then split the data according to task successes and failures. We used full‐path sequence analysis to identify groups of students with similar behavioural patterns in the respective tasks. Double‐checking and minimalistic behaviour was associated with success in CPS, while guessing and exploring task‐irrelevant content was associated with failure. Our findings held for both tasks investigated, from two different CPS measurement frameworks. We thus gained detailed insight into the behavioural processes that are related to success and failure in CPS.
Dieser Entwurf eines Verhaltenskodex richtet sich an Hochschulen, die mittels Learning Analytics die Qualität des Lernens und Lehrens verbessern wollen. Der Kodex kann als Vorlage zur Erstellung von organisationsspezifischen Verhaltenskodizes dienen. Er sollte an Hochschulen, die Learning Analytics einführen wollen, durch Konsultationen mit allen Interessengruppen überprüft und an die Ziele sowie die bestehende Praxis innerhalb der jeweiligen Hochschulen angepasst werden. Der Kodex wurde auf Grundlage einer Analyse bestehender europäischer Kodizes (Engelfriet, Manderveld & Jeunink, 2017; Westerlaken, Manderveld & Jorna, 2019; Sclater & Bailey, 2015; Open University UK, 2014; University of Edinburgh, 2018) und der in Deutschland geltenden Rechtsgrundlage vom Innovationsforum Trusted Learning Analytics des hessenweiten Projektes „Digital gestütztes Lehren und Lernen in Hessen“ entwickelt.
A question of striking the right balance : how do digital media influence how we think and act?
(2020)
What influence do digital technologies have on human perception, thinking and action? Do computer games harm the development of young brains? And is there really such a thing as »digital dementia«, an increasing forgetfulness caused by the use of modern technologies? For some of these questions, answers are available that are empirically corroborated.
Auf das richtige Maß kommt es an : wie beeinflussen digitale Medien unser Denken und Handeln?
(2020)
Welchen Einfluss haben digitale Technologien auf das menschliche Wahrnehmen, Denken und Handeln? Schaden Computerspiele der Entwicklung junger Gehirne? Und gibt es tatsächlich so etwas wie eine »digitale Demenz«, eine durch die Nutzung moderner Technologien bedingte wachsende Vergesslichkeit? Auf einige dieser Fragen gibt es bereits Antworten, die empirisch belegt sind.
Children with reading and/or spelling disorders have increased rates of behavioral and emotional problems and combinations of these. Some studies also find increased rates of attention-deficit/hyperactivity disorder (ADHD), conduct disorder, anxiety disorder, and depression. However, the comorbidities of, e.g., arithmetic disorders with ADHD, anxiety disorder, and depression have been addressed only rarely. The current study explored the probability of children with specific learning disorders (SLD) in reading, spelling, and/or arithmetic to also have anxiety disorder, depression, ADHD, and/or conduct disorder. The sample consisted of 3,014 German children from grades 3 and 4 (mean age 9;9 years) who completed tests assessing reading, spelling as well as arithmetic achievement and intelligence via a web-based application. Psychopathology was assessed using questionnaires filled in by the parents. In children with a SLD we found high rates of anxiety disorder (21%), depression (28%), ADHD (28%), and conduct disorder (22%). Children with SLD in multiple learning domains had a higher risk for psychopathology and had a broader spectrum of psychopathology than children with an isolated SLD. The results highlight the importance of screening for and diagnosing psychiatric comorbidities in children with SLD.
As a relevant cognitive-motivational aspect of ICT literacy, a new construct ICT Engagement is theoretically based on self-determination theory and involves the factors ICT interest, Perceived ICT competence, Perceived autonomy related to ICT use, and ICT as a topic in social interaction. In this manuscript, we present different sources of validity supporting the construct interpretation of test scores in the ICT Engagement scale, which was used in PISA 2015. Specifically, we investigated the internal structure by dimensional analyses and investigated the relation of ICT Engagement aspects to other variables. The analyses are based on public data from PISA 2015 main study from Switzerland (n = 5860) and Germany (n = 6504). First, we could confirm the four-dimensional structure of ICT Engagement for the Swiss sample using a structural equation modelling approach. Second, ICT Engagement scales explained the highest amount of variance in ICT Use for Entertainment, followed by Practical use. Third, we found significantly lower values for girls in all ICT Engagement scales except ICT Interest. Fourth, we found a small negative correlation between the scores in the subscale “ICT as a topic in social interaction” and reading performance in PISA 2015. We could replicate most results for the German sample. Overall, the obtained results support the construct interpretation of the four ICT Engagement subscales.