4.5 Article

Design, development, and evaluation of an individual digital study assistant for higher education students

Publisher

SPRINGER
DOI: 10.1007/s11423-023-10255-8

Keywords

Individual digital study assistant; Higher education institution; Requirement analysis; Prototyping; Evaluation; Action design research

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The increasing number of students in higher education institutions and their diverse educational backgrounds have led to a growing demand for individual study support. The COVID-19 pandemic has also resulted in an increase in online lectures, further emphasizing the need for self-regulated learning. This study focuses on the design, development, and evaluation of an individual digital study assistant (IDSA) that aims to support students' self-regulated learning, study organization, and goal achievement in the early stages of their education.
The growing number of students in higher education institutions, along with students' diverse educational backgrounds, is driving demand for more individual study support. Furthermore, online lectures increased due to the COVID-19 pandemic and are expected to continue, further accelerating the need for self-regulated learning. Individual digital study assistants (IDSA) address these challenges via ubiquitous, easy, automatic online access. This Action Design Research-based study entailed designing, developing, and evaluating an IDSA that aims to support students' self-regulated learning, study organization, and goal achievement for students in their early study phase with limited knowledge of higher education institutions. Therefore, data from 28 qualitative expert interviews, a quantitative survey of 570 students, and a literature review was used to derive seven general IDSA requirements, including functionalities, contact options, data-based responsiveness and individuality, a well-tested system, marketing strategies, data protection, and usability. The research team incorporated the identified requirements into an IDSA prototype, tested by more than 1000 students, that includes functionalities as recommending lectures based on individual interests and competencies, matching students, and providing feedback about strengths and weaknesses in learning behaviors. The results and findings compromise a knowledge base for academics, support IDSA theory building, and illustrate IDSA design and development to guide system developers and decision-makers in higher education. This knowledge can also be transferred to other higher education institutions to support implementing IDSAs with limited adaptations. Further, this research introduces a feasible functional system to support self-organization.

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