Karlsruhe University of Education (Pädagogische Hochschule Karlsruhe) is an institution of higher education in Karlsruhe, Germany. Its focus is on educational processes in social, institutional and cultural contexts. It has approximately 3,742 students, 180 researchers and lecturers and about 90 administrative staff members..
Background: The monitoring of one's own learning progress is a key process in models of self-regulated learning and a key predictor of self-regulated learning and academic success. Judgments of learning (JOLs) are an established measure for assessing people's monitoring of learning and have been found to predict learners' subsequent performance as well as effort regulation. However, most studies have been conducted in laboratory settings, involving relatively artificial learning materials and low-stakes tests. Aims: We evaluate the predictive validity of JOLs for learning performance and effort regulation in an ecologically valid learning environment by requesting aggregate JOLs in an intelligent tutoring system. Sample: 90 German university students used an intelligent tutoring system that provided practice exercises for self-regulated preparation for a statistics exam over the course of a semester. Methods: Aggregate JOLs for each chapter of the statistics course were assessed once per week (279 assessments in total). Dependent variables were learning performance as well as absolute and relative learning effort for each chapter, derived from the intelligent tutoring system's log files. Results: JOLs significantly predicted learning performance (beta = 0.20, p < .001) and effort regulation (beta(absolute) = -0.12, p < .001, beta(relative) = -0.07, p = .002). Conclusions: The present research demonstrates that JOLs have predictive power in real-world learning. It thus bridges the gap between experimental cognitive research and applied educational research on metamemory and self-regulation.
This study examines the effects of full-leg compression sleeves worn during a 90-min recovery period on repeated sprint performance and exercise-induced leg soreness (DOMS) in youth soccer players. Twelve male youth soccer players (17 ± 0 years; 178 ± 7 cm; 70.9 ± 7.5 kg) performed a repeated sprint protocol (5 × 30 m sprints, 20 s recovery; RSP1) followed by a modified Loughborough Intermittent Shuttle Test (LIST) to induce fatigue. After the LIST, players underwent a 90-min passive recovery wearing either full leg compression sleeves (COMP, 19-25 mmHg) or regular gym pants (CON) in a randomized crossover design. After the 90-min recovery, all players repeated the RSP (RSP2), and exercise-induced DOMS was assessed via a visual analogue scale 14 and 24 h post-exercise. Mean sprint times were similar across conditions (RSP1: COMP 4.59 ± 0.16 s, CON 4.65 ± 0.18 s; RSP2: COMP 4.59 ± 0.15 s, CON 4.64 ± 0.19 s), with no significant differences between COMP and CON for performance changes (COMP: +0.01 ± 0.06 s; CON: -0.01 ± 0.05 s) or DOMS (14 h: COMP 3.49 ± 1.73, CON 4.73 ± 2.32; 24 h: COMP 2.78 ± 2.32, CON 4.04 ± 2.12). Compression garments had no impact on repeated sprint performance or exercise-induced leg soreness. The efficacy of compression garments for recovery remains inconclusive, requiring further research.
This paper synthesizes insights from a scoping workshop funded by the Volkswagen Foundation that focused on reading competencies in the digital age. The purpose of the workshop was to discuss the current state of research, identify actionable next steps and outline considerations for future work in the context of learning to read in a digital world. The conference brought together German researchers with a wide range of backgrounds and expertise in reading research including computer science, psychology, language processing and educational science. Presentations and discussions during the conference centred broadly on potentials and challenges of learning to read and reading support in the context of digitalization—focusing on issues related to artificial intelligence and app-based learning. Results of the workshop and subsequent writing sessions include a synthesis of key considerations and core questions for the field of research on digital approaches to support reading. Findings highlight the need for the field at large to identify and develop digital tools for diagnosing readers’ abilities and providing them with the support they need, and to do so with increased interdisciplinary collaboration, open science practices and communication among scholars.
Generative KI-Chatbots wie ChatGPT zeigen neue Möglichkeiten zur Unterstützung von Lernprozessen in der Programmierausbildung, deren Wirksamkeit jedoch von der didaktischen Einbettung abhängt. In einer Pilotstudie entwickelten Studierende ein Arduino-Projekt mithilfe von ChatGPT. Analysiert wurden sowohl die erstellten Programme der Studierenden als auch ihre Logbücher zur Promptnutzung. Die Logbücher wurden anhand eines literaturgestützten Kategoriensystems effektiver Prompts kodiert. Die Ergebnisse zeigen, dass die Prompts meist unpräzise, kaum kontextualisiert und selten iterativ weiterentwickelt wurden. Studierende übernahmen den generierten Programmcode häufig, ohne dessen Funktionslogik zu verstehen, was sich in Schwierigkeiten beim Erkennen und Beheben von Codefehlern zeigte. Die Befunde deuten darauf hin, dass eine rein ChatGPT-basierte Programmierung den Wissenserwerb von Novizinnen und Novizen kaum fördert oder ihn erschweren kann.
