Menü Überspringen
Contact
Deutsch
English
Not track
Data Protection
Search
Log in
DIPF News
Research
Infrastructures
Institute
Zurück
Contact
Deutsch
English
Not track
Data Protection
Search
Home
>
Research
>
Publications
>
Publications Data Base
Search results in the DIPF database of publications
Your query:
(Personen: "Drachsler," und "Hendrik")
Advanced Search
Search term
Only Open Access
Search
Unselect matches
Select all matches
Export
219
items matching your search terms.
Show all details
LAxplore: An NLP-based tool for distilling learning analytics and learning design instruments out […]
Ahmad, Atezaz; Schneider, Jan; Schiffner, Daniel; Islamovic, Esad; Drachsler, Hendrik
Book Chapter
| Aus: Fred, Ana; Coenen, Frans; Bernardino, Jorge (Hrsg.): Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, November 13-15, in Rome, Italy | Setúbal: SciTePress | 2023
44460 Endnote
Author(s):
Ahmad, Atezaz; Schneider, Jan; Schiffner, Daniel; Islamovic, Esad; Drachsler, Hendrik
Title:
LAxplore: An NLP-based tool for distilling learning analytics and learning design instruments out of scientific publications
In:
Fred, Ana; Coenen, Frans; Bernardino, Jorge (Hrsg.): Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, November 13-15, in Rome, Italy, Setúbal: SciTePress, 2023 , S. 230-239
DOI:
10.5220/0012163600003598
URL:
https://www.scitepress.org/Link.aspx?doi=10.5220/0012163600003598
Publication Type:
4. Beiträge in Sammelbänden; Sammelband (keine besondere Kategorie)
Language:
Englisch
Abstract (english):
Each year, the amount of research publications is increasing. Staying on top of the state of the art is a pressing issue. The field of Learning Analytics (LA) is no exception, with the rise of digital education systems that are used broadly these days from K12 up to Higher Education. Keeping track of the advances in LA is challenging. This is especially the case for newcomers to the field, as well as for the increasing number of LA units that consult their teachers and scholars on applying evidence-based research outcomes in their lectures. To keep an overview of the rapidly growing research findings on LA, we developed LAxplore, a tool that uses NLP to extract relevant information from the LA literature. In this article, we present the evaluation of LAxplore. Results from the evaluation show that LAxplore can significantly support researchers in extracting information from relevant LA publications as it reduces the time of searching and retrieving the knowledge by a factor of six. However, the accurate extraction of relevant information from LA literature is not yet ready to be fully automatized and some manual work is still required.
DIPF-Departments:
Informationszentrum Bildung
A trusted learning analytics dashboard for displaying OER
Ahmad, Atezaz; Yordanov, Ivaylo Ivanov; Yau, Jane; Schneider, Jan; Drachsler, Hendrik
Book Chapter
| Aus: Otto, Daniel; Scharnberg, Gianna; Kerres, Michael; Zawacki-Richter, Olaf (Hrsg.): Distributed learning ecosystems: Concepts, resources, and repositories | Wiesbaden: Springer | 2023
43376 Endnote
Author(s):
Ahmad, Atezaz; Yordanov, Ivaylo Ivanov; Yau, Jane; Schneider, Jan; Drachsler, Hendrik
Title:
A trusted learning analytics dashboard for displaying OER
In:
Otto, Daniel; Scharnberg, Gianna; Kerres, Michael; Zawacki-Richter, Olaf (Hrsg.): Distributed learning ecosystems: Concepts, resources, and repositories, Wiesbaden: Springer, 2023 , S. 279-303
DOI:
10.1007/978-3-658-38703-7_15
URL:
https://link.springer.com/chapter/10.1007/978-3-658-38703-7_15
Publication Type:
4. Beiträge in Sammelbänden; Sammelband (keine besondere Kategorie)
Language:
Englisch
Keywords:
Datenanalyse; Datenerfassung; Indikator; Internetplattform; Learning Analytics; Lernplattform; Literaturbericht; Open Educational Resources; Technologie
Abstract:
Learning Analytics (LA) consists of miscellaneous steps that include data harvesting, storing, cleaning, anonymisation, mining, analysis, and visualisation so that the vast amount of educational data is comprehensible and ethically utilisable by educators or instructors to obtain the advantages and benefits that LA can bring to the educational scene. These include the potential to increase learning experiences and reduce dropout rates. In this chapter, we shed light on OER repositories, LA, and LA dashboards and present an implementation of a research-driven LA dashboard for displaying OER and their repositories that allows the visualisation of educational data in an understandable way for both educators and learners. Moreover, we present an LA dashboard for displaying OER that shows information about the existing German OER repositories as part of our EduArc project located in Germany. The LA dashboard consists of multiple adopted indicators and metrics such as the number of reading sessions, duration of reading sessions, number of reading interruptions, number of learning activities, student attendance, and student grades. The details of the research methodology, including a literature review to create this dashboard, as well as the display items of the dashboard are presented and further elaborated. (DIPF/Autor)
DIPF-Departments:
Informationszentrum Bildung
Detecting the disengaged reader. Using scrolling data to predict disengagement during reading
Biedermann, Daniel; Schneider, Jan; Ciordas-Hertel, George-Petru; Eichmann, Beate; Hahnel, Carolin; […]
Book Chapter
| Aus: Hilliger, Isabel, Khosravi, Hassan; Rienties, Bart; Dawson, Shane (Hrsg.): LAK23 Conference Proceedings: The Thirteenth International Conference on Learning Analytics & Knowledge, March 13-17, 2023, Hybrid, Arlington, Texas, USA | New York; NY: Association for Computing Machinery | 2023
43666 Endnote
Author(s):
Biedermann, Daniel; Schneider, Jan; Ciordas-Hertel, George-Petru; Eichmann, Beate; Hahnel, Carolin; Goldhammer, Frank; Drachsler, Hendrik
Title:
Detecting the disengaged reader. Using scrolling data to predict disengagement during reading
In:
Hilliger, Isabel, Khosravi, Hassan; Rienties, Bart; Dawson, Shane (Hrsg.): LAK23 Conference Proceedings: The Thirteenth International Conference on Learning Analytics & Knowledge, March 13-17, 2023, Hybrid, Arlington, Texas, USA, New York; NY: Association for Computing Machinery, 2023 , S. 585-591
DOI:
10.1145/3576050.3576078
URL:
https://dl.acm.org/doi/10.1145/3576050.3576078
Publication Type:
4. Beiträge in Sammelbänden; Beiträge in Proceedings mit Peer-Review-System
Language:
Englisch
Abstract:
When reading long and complex texts, students may disengage and miss out on relevant content. In order to prevent disengaged behavior or to counteract it by means of an intervention, it is ideally detected an early stage. In this paper, we present a method for early disengagement detection that relies only on the classification of scrolling data. The presented method transforms scrolling data into a time series representation, where each point of the series represents the vertical position of the viewport in the text document. This time series representation is then classified using time series classification algorithms. We evaluated the method on a dataset of 565 university students reading eight different texts. We compared the algorithm performance with different time series lengths, data sampling strategies, the texts that make up the training data, and classification algorithms. The method can classify disengagement early with up to 70% accuracy. However, we also observe differences in the performance depending on which of the texts are included in the training dataset. We discuss our results and propose several possible improvements to enhance the method. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung; Lehr und Lernqualität in Bildungseinrichtungen
Digitalisierung und Diagnostik in Schulen - Herausforderungen für Bildungspraxis und […]
Jude, Nina; Ziehm, Jeanette; Goldhammer, Frank; Drachsler, Hendrik; Hasselhorn, Marcus
Book Chapter
| Aus: Scheiter, Katharina; Gogolin, Ingrid (Hrsg.): Bildung für eine digitale Zukunft | Wiesbaden: Springer | 2023
42509 Endnote
Author(s):
Jude, Nina; Ziehm, Jeanette; Goldhammer, Frank; Drachsler, Hendrik; Hasselhorn, Marcus
Title:
Digitalisierung und Diagnostik in Schulen - Herausforderungen für Bildungspraxis und Bildungsforschung
In:
Scheiter, Katharina; Gogolin, Ingrid (Hrsg.): Bildung für eine digitale Zukunft, Wiesbaden: Springer, 2023 (Edition ZFE, 15), S. 275-292
DOI:
10.1007/978-3-658-37895-0_11
URL:
https://link.springer.com/chapter/10.1007/978-3-658-37895-0_11
Publication Type:
4. Beiträge in Sammelbänden; Sammelband (keine besondere Kategorie)
Language:
Deutsch
Abstract:
Im Frühjahr 2020 wurden Schulen unerwartet vor die Herausforderung gestellt, Unterricht und Schulentwicklung vor dem Hintergrund kontinuierlicher pandemiebedingter Disruptionen zu ermöglichen. Unterricht vor Ort wurde ersetzt durch digitale Formate des Lernens und der Kommunikation auf Distanz. Für die Bildungspraxis erweisen sich dabei die Herausforderungen im Bereich der digitalen Schulverwaltung, des digitalen Lernens und der Diagnostik von Lernfortschritten als besonders relevant. Insbesondere die computergestützte Diagnostik bietet großes Potenzial, um Erkenntnisse nicht nur über Lernergebnisse, sondern auch Lernprozesse zu generieren. Im Bereich der Bildungsforschung interessiert, wie Lernen durch digitale Medien gestaltet werden kann und wie die dabei generierten Daten für die Bildungspraxis gewinnbringend genutzt werden können. Dieser Beitrag beschreibt die Herausforderungen und Potenziale, die sich im Bereich von computerbasierter, lernbegleitender Diagnostik gegenwärtig zeigen. Diese liegen insbesondere in der flächendeckenden Einführung entsprechender Instrumente in den Schulen sowie der Aus- und Weiterbildung von Lehrpersonen im Umgang mit diesen. Darauf aufbauend werden Bedarfe der Bildungspraxis und Desiderata der Bildungsforschung gegenübergestellt und auf Synergiepotenziale hingewiesen. (DIPF/Orig.)
DIPF-Departments:
Bildung und Entwicklung; Informationszentrum Bildung; Lehr und Lernqualität in Bildungseinrichtungen
Digitalisierung und Diagnostik in Schulen - Herausforderungen für Bildungspraxis und […]
Jude, Nina; Ziehm-Eicher, Jeanette; Goldhammer, Frank; Drachsler, Hendrik; Hasselhorn, Marcus
Book Chapter
| Aus: Scheiter, Katharina; Gogolin, Ingrid (Hrsg.): Bildung für eine digitale Zukunft | Wiesbaden: Springer VS | 2023
43747 Endnote
Author(s):
Jude, Nina; Ziehm-Eicher, Jeanette; Goldhammer, Frank; Drachsler, Hendrik; Hasselhorn, Marcus
Title:
Digitalisierung und Diagnostik in Schulen - Herausforderungen für Bildungspraxis und Bildungsforschung
In:
Scheiter, Katharina; Gogolin, Ingrid (Hrsg.): Bildung für eine digitale Zukunft, Wiesbaden: Springer VS, 2023 (Edition ZfE, 15), S. 275-292
DOI:
10.1007/978-3-658-37895-0_11
URL:
https://link.springer.com/chapter/10.1007/978-3-658-37895-0_11
Publication Type:
4. Beiträge in Sammelbänden; Sammelband (keine besondere Kategorie)
Language:
Deutsch
Abstract:
Im Frühjahr 2020 wurden Schulen unerwartet vor die Herausforderung gestellt, Unterricht und Schulentwicklung vor dem Hintergrund kontinuierlicher pandemiebedingter Disruptionen zu ermöglichen. Unterricht vor Ort wurde ersetzt durch digitale Formate des Lernens und der Kommunikation auf Distanz. Für die Bildungspraxis erweisen sich dabei die Herausforderungen im Bereich der digitalen Schulverwaltung, des digitalen Lernens und der Diagnostik von Lernfortschritten als besonders relevant. Insbesondere die computergestützte Diagnostik bietet großes Potenzial, um Erkenntnisse nicht nur über Lernergebnisse, sondern auch Lernprozesse zu generieren. Im Bereich der Bildungsforschung interessiert, wie Lernen durch digitale Medien gestaltet werden kann und wie die dabei generierten Daten für die Bildungspraxis gewinnbringend genutzt werden können. Dieser Beitrag beschreibt die Herausforderungen und Potenziale, die sich im Bereich von computerbasierter, lernbegleitender Diagnostik gegenwärtig zeigen. Diese liegen insbesondere in der flächendeckenden Einführung entsprechender Instrumente in den Schulen sowie der Aus- und Weiterbildung von Lehrpersonen im Umgang mit diesen. Darauf aufbauend werden Bedarfe der Bildungspraxis und Desiderata der Bildungsforschung gegenübergestellt und auf Synergiepotenziale hingewiesen. (DIPF/Orig.)
DIPF-Departments:
Bildung und Entwicklung; Informationszentrum Bildung; Lehr und Lernqualität in Bildungseinrichtungen
Lernpfade in adaptiven und künstlich-intelligenten Lernprogrammen. Eine kritische Analyse aus […]
Kerres, Michael; Buntins, Katja; Buchner, Josef; Drachsler, Hendrik; Zawacki-Richter, Olaf
Book Chapter
| Aus: Witt, Claudia de; Gloerfeld, Christina; Wrede, Silke E. (Hrsg.): Künstliche Intelligenz in der Bildung | Wiesbaden: Springer VS | 2023
43753 Endnote
Author(s):
Kerres, Michael; Buntins, Katja; Buchner, Josef; Drachsler, Hendrik; Zawacki-Richter, Olaf
Title:
Lernpfade in adaptiven und künstlich-intelligenten Lernprogrammen. Eine kritische Analyse aus mediendidaktischer Sicht
In:
Witt, Claudia de; Gloerfeld, Christina; Wrede, Silke E. (Hrsg.): Künstliche Intelligenz in der Bildung, Wiesbaden: Springer VS, 2023 , S. 109-131
DOI:
10.1007/978-3-658-40079-8_6
URL:
https://link.springer.com/chapter/10.1007/978-3-658-40079-8_6
Publication Type:
4. Beiträge in Sammelbänden; Sammelband (keine besondere Kategorie)
Language:
Deutsch
Abstract:
Der Beitrag kontrastiert interaktive, adaptive sowie künstlich-intelligente Lernprogramme. Adaptive und KI-basierte Anwendungen erweisen sich in der Entwicklung als aufwändiger und haben sich bislang nicht durchsetzen können. Um die Chancen dieser Technologien abzuschätzen, werden ihre Möglichkeiten verglichen. Adaptive Lernprogramme eignen sich vor allem für den Erwerb von Fertigkeiten, KI-basierte Lösungen, wenn sich ein Expertisemodell nicht explizieren lässt. Benannt werden didaktische und pädagogische Herausforderungen, denen sich KI-basierte Lernanwendungen künftig stellen müssen.
DIPF-Departments:
Informationszentrum Bildung
Why you should give your students automatic process feedback on their collaboration. Evidence from […]
Menzel, Lukas; Gombert, Sebastian; Weidlich, Joshua; Fink, Aron; Frey, Andreas; Drachsler, Hendrik
Book Chapter
| Aus: Viberg, Olga; Jivet, Ioana; Muñoz-Merino, Pedro; Perifanou, Maria; Papathoma, Tina (Hrsg.): Responsive and sustainable educational futures: 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Aveiro, Portugal, September 4-8, 2023, proceedings | Cham: Springer | 2023
44077 Endnote
Author(s):
Menzel, Lukas; Gombert, Sebastian; Weidlich, Joshua; Fink, Aron; Frey, Andreas; Drachsler, Hendrik
Title:
Why you should give your students automatic process feedback on their collaboration. Evidence from a randomized experiment
In:
Viberg, Olga; Jivet, Ioana; Muñoz-Merino, Pedro; Perifanou, Maria; Papathoma, Tina (Hrsg.): Responsive and sustainable educational futures: 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Aveiro, Portugal, September 4-8, 2023, proceedings, Cham: Springer, 2023 (Lecture Notes in Computer Science, 14200), S. 198-212
DOI:
10.1007/978-3-031-42682-7_14
URL:
https://link.springer.com/chapter/10.1007/978-3-031-42682-7_14
Publication Type:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Language:
Englisch
Abstract:
In Computer-Supported Collaborative Learning (CSCL), students learn in small groups to achieve learning benefits outside what would be possible for individual students. As in other forms of learning, students need feedback on the quality of their work. Still, writing high-quality informative feedback requires time on the part of educators. This makes it less feasible to provide quality feedback at scale. Given the importance of group dynamics in CSCL, quality feedback should also contain information about group processes and discussion quality. Emergent roles provide a natural anchor point for this. We propose a method to automatically deliver highly informative, textual process feedback for CSCL forum discussion tasks in an introductory teacher education class, focusing on individual students' group communication. This feedback is generated from several discourse indicators, that are used to derive emergent roles of the students. From that we derive feedback about strengths and potential for improvement. In a randomized control trial, we show that the highly informative feedback generated with our method is preferred by the students. Implications and avenues for future research are discussed in light of these findings.
DIPF-Departments:
Informationszentrum Bildung
Measuring collaboration quality through audio data and learning analytics
Praharaj, Sambit; Scheffel, Maren; Specht, Marcus; Drachsler, Hendrik
Book Chapter
| Aus: Kovanovic, Vitomir; Azevedo, Roger; Gibson, David C.; lfenthaler, Dirk (Hrsg.): Unobtrusive observations of learning in digital environments: Advances in analytics for learning and teaching | Cham: Springer | 2023
43789 Endnote
Author(s):
Praharaj, Sambit; Scheffel, Maren; Specht, Marcus; Drachsler, Hendrik
Title:
Measuring collaboration quality through audio data and learning analytics
In:
Kovanovic, Vitomir; Azevedo, Roger; Gibson, David C.; lfenthaler, Dirk (Hrsg.): Unobtrusive observations of learning in digital environments: Advances in analytics for learning and teaching, Cham: Springer, 2023 (Advances in Analytics for Learning and Teaching), S. 91-110
DOI:
10.1007/978-3-031-30992-2_6
URL:
https://link.springer.com/chapter/10.1007/978-3-031-30992-2_6
Publication Type:
4. Beiträge in Sammelbänden; Sammelband (keine besondere Kategorie)
Language:
Englisch
Abstract:
Collaboration is an important twenty-first-century skill. Collaboration quality detection can help to support collaboration. This chapter addresses the collaboration quality detection and measurement: (1) to define collaboration quality using audio data and unobtrusive learning analytics measures; (2) to explain the design of a sensor-based set up for automatic collaboration analytics; (3) to move toward quantifying the quality of collaboration by using this set up and show the analysis using meaningful visualizations. Furthermore, we address the challenges and issues at hand and how solutions can be built upon the work already done. To elaborate the different chapter's objectives, we use the terminology of indicators (i.e., the events) and indexes (i.e., the process) to define the components to detect collaboration quality. In one study, during collaborative brainstorming, higher was the equality (i.e., the index) of total speaking time (i.e., the indicator), lower was the dominance of each group member (in terms of total speaking time), and better was the quality of collaboration. However, quality of collaboration is dependent on the context of collaboration and the actual content of the discussion. During collaboration content analysis has been mostly on the surface level by using certain representative keywords to model different topic clusters. Therefore, we develop a sensor-based setup for automatic collaboration analytics to understand collaboration quality holistically in a learning context. Here, our aim is to understand "how" group members speak (i.e., speaking time indicator) and "what'" (i.e., the content of the conversations) group members speak to move toward collaboration quality measurement. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
Designing an app to enhance children's planning skills. A case for personalized technology
Biedermann, Daniel; Breitwieser, Jasmin; Nobbe, Lea; Drachsler, Hendrik; Brod, Garvin
Working Papers
| 2023
43943 Endnote
Author(s):
Biedermann, Daniel; Breitwieser, Jasmin; Nobbe, Lea; Drachsler, Hendrik; Brod, Garvin
Title:
Designing an app to enhance children's planning skills. A case for personalized technology
Published:
Charlottesville; VA: PsyArXiv Preprints, 2023
DOI:
10.31234/osf.io/ak3d7
URL:
https://osf.io/preprints/psyarxiv/ak3d7/
Publication Type:
5. Arbeits- und Diskussionspapiere; weitere Arbeits- und Diskussionspapiere
Language:
Englisch
Abstract:
Planning is an important but difficult self-regulation strategy. The successful implementation of a plan requires that the plan is retrievable in everyday life when it is needed. Children in particular are unlikely to use effective strategies to internalize plans in a way that makes them easy to remember. Therefore, we designed PROMPT, a planning app to help children create and internalize plans effectively. The app included different internalization activities that were hypothesized to promote deeper or shallower processing of plans. School-aged children (N = 106, 9-14 years) used PROMPT for 27 days in their daily lives. Contrary to our hypotheses, the type of internalization activity was not associated with memory success overall. Deeper processing activities were only effective for children who spent more time performing these activities, suggesting that there were differences in how effectively children could make use of the internalization activities. These individual differences were predicted by children's grade level and their analogical reasoning abilities, and mediated by time on task. Findings suggest that a child-appropriate planning app needs to be personalized to be effective; internalization activities have to be tailored to children's learning prerequisites. (DIPF/Orig.)
DIPF-Departments:
Bildung und Entwicklung; Informationszentrum Bildung
Learning analytics in the age of AI
Drachsler, Hendrik; Rienties, Bart; Rabin, Eyal
Working Papers
| 2023
44456 Endnote
Author(s):
Drachsler, Hendrik; Rienties, Bart; Rabin, Eyal
Title:
Learning analytics in the age of AI
Published:
2023
URL:
https://open.spotify.com/episode/5MMqdLhJoJcnwy9jSFDIN2?si=0d64ada4b61e4017&nd=1&dlsi=44dc68d0ceb445fa
Publication Type:
7. Blogbeiträge; Pod-; Vidcasts; Pod-/Vidcasts
Language:
Englisch
DIPF-Departments:
Informationszentrum Bildung
Unselect matches
Select all matches
Export
<
1
2
3
4
...
20
>
Show all
(219)