Paper and presentation about the topic of detecting disengaged reading at LAK23

Paper and presentation about the topic of detecting disengaged reading at LAK23

Conference, Conference, Event, Higher Education, Publication, Research topic, Self-Regulation, Target group
At the recent Learning Analytics and Knowledge Conference (LAK23), Daniel Biedermann presented his paper "Detecting the Disengaged Reader - Using Scrolling Data to Predict Disengagement during Reading," to shed light on the potential for early detection of disengagement in readers. The paper presents a unique method for early disengagement detection that relies solely on the classification of scrolling data. By transforming scrolling data into a time series representation, each point of the series represents the vertical position of the viewport in the text document. Time series classification algorithms are then used to evaluate the data.The results were promising, with the method able to classify disengagement early with up to 70% accuracy. However, the study also observed differences in performance depending on which texts were included in the training dataset. Biedermann…
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Invited talks about providing feedback with learning analytics

Invited talks about providing feedback with learning analytics

Assessment, Feedback, General education, Invited talk, Learning Analytics, Self-Regulation
In the month of November, Ioana Jivet was invited to share her work on two occasions. The first was an invited lecture in the course FDH3006 Introduction to Learning Analytics part of a PhD Program at KTH Stockholm in collaboration with the University of Bergen, Norway and the University of Copenhagen, Denmark. The talk covered the topic of "Generating highly informative feedback with learning analytics" and addressed the question of how we can design effective feedback to students in online environments using learning analytics. The second talk was given as part of the event 100 DAYS OF... Data for Learning organised by the Centre for Education and Learning at TU Delft. The presentation covered the topic of student facing-learning analytics and goal setting. The talk was recorded and is available…
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Presentation: Atezaz participated in the ICDLE conference and presented a new publication

Presentation: Atezaz participated in the ICDLE conference and presented a new publication

Artificial Intelligence, Conference, Conference, Feedback, Further Education, Learning Analytics, Lifelong Learning, Open access, Publication, Self-Regulation
Our paper titled "Caught in the Lifelong Learning Maze: Helping People with Learning Analytics and Chatbots to Find Personal Career Paths" was accepted at the 13th International Conference on Distance Learning and Education (ICDLE 2022) held at the University of Barcelona, Spain. Atezaz Ahmad participated in the conference and presented their publication. The article will be published (open access) in the International Journal of Information and Education Technology. Abstract: Current lifelong learning platforms offer users a query option to select a wide variety of courses. However, finding a suitable course among the seemingly endless catalogs of options presented by the platforms is not straightforward. We argue that digital counseling can enhance this process. In this paper, we present a set of three formative studies where we explored the main aspects…
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New Pub: Tools Designed to Support Self-Regulated Learning in Online Learning Environments: A Systematic Review

New Pub: Tools Designed to Support Self-Regulated Learning in Online Learning Environments: A Systematic Review

Higher Education, Journal, Learning Analytics, Self-Regulation
Self-regulated learning (SRL) is a crucial higher-order skill required by learners of the 21st century, who will need to become lifelong learners to adapt to the continually changing environments. Literature provides examples of tools for scaffolding SRL in online environments. In this study, we provide the state-of-the-art concerning tools that support SRL in terms of theoretical models underpinning development, supported SRL processes, tool functionalities, used data and visualizations. We reviewed 42 articles published between 2008 and 2020, including information from 25 tools designed to support SRL. Our findings indicate that (1) many of the studies do not explicitly specify the SRL theoretical model used to guide the design process of the tool; (2) goal setting, monitoring, and self-evaluation are the most prevalent SRL processes supported through functionalities such as content…
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New Pub: Connecting the dots – A literature review on learning analytics indicators from a learning design perspective

New Pub: Connecting the dots – A literature review on learning analytics indicators from a learning design perspective

Empirical Study, Higher Education, Journal, Learning Analytics, Learning Design, Lifelong Learning, Literature review, Open access, Publication, Self-Regulation, Special Issue, Target group
[caption id="attachment_4329" align="alignright" width="450"] Occurrences of the most commonly used learning analytic indicators over the past 10 years[/caption] Background: During the past decade, the increasingly heterogeneous field of learning analytics has been critiqued for an over-emphasis on data-driven approaches at the expense of paying attention to learning designs. Method and objective: In response to this critique, we investigated the role of learning design in learning analytics through a systematic literature review. 161 learning analytics (LA) articles were examined to identify indicators that were based on learning design events and their associated metrics. Through this research, we address two objectives. First, to achieve a better alignment between learning design and learning analytics by proposing a reference framework, where we present possible connections between learning analytics and learning design. Second, to present how…
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Presentation about detecting off-task behavior during learning at the GEBF 2022

Presentation about detecting off-task behavior during learning at the GEBF 2022

Conference, Event, Higher Education, Learning Analytics, Research topic, Self-Regulation
On 09.03.2022, Daniel Biedermann gave a presentation on the topic of recognizing off-task behavior as part of the GEBF conference. The talk was part of the symposium on "Self-Regulation in Learning in Digital Environments: From Problems to Solutions". The talk presented the endeavor of using process data within a learning environment to detect and predict off-task behavior. Special attention was given to the challenges that arise when detecting off-task behavior. The same observed activity may be considered off-task in one case, but relevant to learning in another. Making this distinction requires a precise grasp of the context in which the observed behavior takes place. Aspects such as what phase of learning was someone in when another web page was accessed? Had the learning material already been processed? Or was the…
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