EKM 2024 Abstracts

Area 1 - Educational Knowledge Management
Full Papers

Area 1 - Educational Knowledge Management

Full Papers
Paper Nr: 5
Title:

Learning Analytics Support in Higher-Education: Towards a Multi-Level Shared Learning Analytics Framework
Authors:

Michael Vierhauser, Iris Groher, Clemens Sauerwein, Tobias Antensteiner and Sebastian Hatmanstorfer
Abstract: Assurance of Learning and Competency-Based Education are increasingly important in higher education, not only for accreditation or transfer of credit points. Learning Analytics is crucial for making educational goals measurable and actionable, which is beneficial for program managers, course instructors, and students. While universities typically have an established tool landscape where relevant data is managed, information is typically scattered across various systems with different responsibilities and often only limited capabilities for sharing data. This diversity, however, significantly hampers the ability to analyze data, both on the course and curriculum level. To address these shortcomings and to provide program managers, course instructions, and students with valuable insights, we devised an initial concept for a Multi-Level Shared Learning Analytics Framework to provide consistent definition and measurement of learning objectives, as well as tailored information, visualization, and analysis for different stakeholders. In this paper, we present the results of initial interviews with stakeholders, devising core features. In addition, we assess potential risks and concerns that may arise from the implementation of such a framework and data analytics system. As a result, we identified six essential features and six main risks to guide further requirements elicitation and development of our proposed framework.
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Paper Nr: 6
Title:

ConstrucTED: Constructing Tailored Educational Datasets from Online Courses
Authors:

Aymen A. Bazouzi, Zoltan Miklos, Mickaël Foursov and Hoël Le Capitaine
Abstract: Researchers are actively involved in developing various systems to support education, including recommender systems. However, to create and evaluate such systems, they require rich and versatile datasets about educational content. At times, the available data proves insufficient, leading researchers to invest significant time in crafting personalized web scrapers for additional data retrieval. The generated datasets are often task-specific and may be time-consuming to adapt to future tasks. Additionally, researchers may encounter licensing issues when using courses from different providers. Furthermore, researchers prefer evaluating their methods through diverse tests, involving datasets with varying characteristics. However, this diversity is not commonly found in most available datasets, at least not explicitly so. To address these challenges, we introduce ConstrucTED, a tool built on top of Google APIs, enabling the efficient creation of custom educational datasets from YouTube playlists. This allows datasets to be tailored to specific characteristics such as a predetermined number of courses, coverage of specific topics, or courses from a particular university. ConstrucTED creates datasets from video course transcripts, providing a ready-to-use solution that significantly shortens the time required to create such datasets. The resulting datasets are versatile and suitable for tasks like classification and learning path creation.
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Paper Nr: 9
Title:

Navigating the Landscape of Digital Competence Frameworks: A Systematic Analysis of AI Coverage and Adaptability
Authors:

Barbara Wimmer, Irene Mayr and Thorsten Händler
Abstract: The rapidly evolving capabilities of generative artificial intelligence (AI) in understanding and generating texts and images challenge the role of human competences in existing and redesigned processes and infrastructures in many domains. In addition to aspects such as automating complex tasks and decision-making processes, the question arises as to which human competences are required to deal efficiently and confidently with these newly emerging AI-driven opportunities, manifesting in form of new tools, methods, processes and infrastructures, including the design and use of hybrid human-AI ecosystems. A variety of digital competence frameworks (DCFWs) is available to support practitioners from didactic and business contexts in specifying and measuring such competences. In this paper, we systematically analyze established DCFWs and compare the provided means to cope with the challenges from rapidly evolving generative AI. For this purpose, we present the results of a systematic mapping study (SMS) based on 25 identified international DCFWs, focusing on the degree of AI coverage and adaptability. The resulting structural overview and comparative analysis provides orientation and aims to empower both individual practitioners and organizations to evaluate, select, combine, contextualize, adapt and apply existing frameworks based on their individual application purposes.
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Paper Nr: 10
Title:

Towards Task-Oriented ICALL: A Criterion-Referenced Learner Dashboard Organising Digital Practice
Authors:

Leona Colling, Ines Pieronczyk, Cora Parrisius, Heiko Holz, Stephen Bodnar, Florian Nuxoll and Detmar Meurers
Abstract: Practice is an essential part of learning. Intelligent Computer-Assisted Language Learning (ICALL) systems can provide practice opportunities and give insights into the learner’s learning state and progress. Open learner models have been designed to provide learners with information on the overall learning domain. However, current approaches to foreign language teaching typically motivate practice as preparation for a communicative or functional task. This raises the question of how this motivating functional task context and progress towards mastering the task-essential language can be made explicit in an ICALL system. We present an approach to ICALL practice that is orchestrated in a dashboard that provides information on the learner’s competence-oriented learning progress towards the overall task goals. The dashboard allows students to choose what to practice next based on this information, which provides a transparent, motivating link to the purpose of practicing. Organising digital practice based on a task- and competence-oriented curriculum also facilitates the acceptance of ICALL in the formal school setting. The dashboard introduced in this article extends the intelligent tutoring system FeedBook for English in German secondary schools. The article provides the theoretical background for the dashboard’s structure, motivates the design process, and describes the resulting implementation.
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