Technology-mediated personalised learning for younger learners

Vanbecelaere, Stefanie; Cornillie, Frederik; Depaepe, Fien; Guerrero, Roger Gilabert; Mavrikis, Manolis; Vasalou, Asimina; Benton, Lauren

doi:10.1145/3397617.3398059

Cited by 46 publications

(6 citation statements)

References 19 publications

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“…According to Böhme et al (2020), the aims of using digital media in schools are, on the one hand, the promotion of a critical use of digital media and, on the other hand, the support of learning. Especially in highly heterogeneous inclusive school settings, there is a great potential of digital media, as digital media have the potential to increase the participation of all students in the classroom (Vanbecelaere et al, 2020;Schaumburg, 2021). In this context, digital media can support teachers with diagnostic information and thus foster individualized learning offers (Schaumburg, 2021).…”

Section: Digital Learning Platforms For Individualized Practicementioning

confidence: 99%

“…This is especially relevant for primary schools due to their high heterogeneity (Schwab et al, 2017). The usage of DLP contributes to the ability of all learners to participate in the classroom (Vanbecelaere et al, 2020;Schaumburg, 2021). Regarding the support of learners, DLP hold an added value of particular importance: the availability of learning data.…”

Section: Introductionmentioning

confidence: 99%

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To use or not to use learning data: A survey study to explain German primary school teachers’ usage of data from digital learning platforms for purposes of individualization

Hase

Kahnbach²,

Kuhl³

et al. 2022

Front. Educ.

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Digital learning platforms (DLP) provide various types of information about student learning when used for learning and practice. This learning data holds potential for individualized instruction, which has become increasingly necessary for adequately addressing learners’ individual needs. For primary schools in particular, this is important for developing inclusive schools. However, despite the potential of DLP and the learning data that can be obtained from them, they are rarely used by teachers. Furthermore, little is known about factors that lead teachers to use learning data for instruction and individual support. To address this research gap, we conducted an online cross-sectional survey study of N = 272 primary school teachers in Germany. After describing the respondents’ current and previous usage of learning data from DLP, we used structural equation modeling (SEM) to test the influence of predictors on respondents’ intention to use as well as their usage of learning data from DLP. Finally, we discuss the need for increased usage of learning data in teacher education and training, contributing to ongoing debates about the usage of digital learning data in educational research and practice.

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Section: Digital Learning Platforms For Individualized Practicementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

To use or not to use learning data: A survey study to explain German primary school teachers’ usage of data from digital learning platforms for purposes of individualization

Hase

Kahnbach²,

Kuhl³

et al. 2022

Front. Educ.

View full text Add to dashboard Cite

show abstract

“…Recent serious games have begun to include an adaptive component that makes it possible to personalise the learning path of the game's user through complex algorithms. Beyond the ongoing debate about the exact definition of the more general concept of personalization (Vanbecelaere, Vasalou, et al., 2020), adaptivity is defined here as the ability of a system to adjust instruction based on learner abilities and/or preferences, at any particular point of the instruction process, with the goal of acting on identified learner characteristics and improving the efficiency and efficacy of learning (Oxman & Wong, 2014; Vandewaetere et al., 2011). Hence, it allows for the automatic adaptation of game elements such as content, user interfaces, game mechanics or game difficulty in order to customise or personalise the interactive experience (Holmes et al., 2018; Streicher & Smeddinck, 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

Algorithmic versus teacher‐led sequencing in a digital serious game and the development of second language reading fluency and accuracy

Serra¹,

Gilabert²

2021

Brit J Educational Tech

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Recent years have seen a surge of calls for personalization of education. Automatised adaptivity in serious games has been advocated as a potential instantiation of such calls. Yet little is known about the extent to which personalised learning through automatised adaptivity poses an advantage for language learning over generalised teacher‐led sequencing in digital, game‐based learning environments. The goal of this paper is to address this question by comparing the learning outcomes in reading accuracy and fluency of didactic sequences designed by EFL teachers or by an adaptive algorithm. A total of 67 participants completed several proficiency and reading skills pretest and posttest and used the iRead system for 6 months. Results showed that all learners made progress in reading skills, but no significant differences were found between the two sequences in relation to the development of reading skills. It was also shown that adaptivity works best if it leads to increase in the number of games per feature. Results are discussed in the context of previous findings, and the role of adaptivity and sequencing is critically assessed. What is already known about this topic? Serious games have the potential to aid learning but empirical research is needed. Findings about the efficiency of serious games are mixed. Current and reviewed versions of the Simple View of Reading constitute a suitable framework to measure reading acquisition. What this paper adds? It contributes to the growing corpus of research on digital serious games. It provides empirical evidence on the use of an adaptive system in formal education. Comparing a teacher‐led sequence to an algorithmic adaptive sequence on the same digital serious game has never been done before. The paper shows the need to obtain both system‐internal and system‐external data in order to capture the impact of gameplay on the development of L2 reading skills. Implications for practise and/or policy It sheds some light on how certain game designs may actually help practise with different degrees of intervention by teachers. It is interesting for teachers to use an adaptive sequence that they can check and intervene in if needed.

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“…Rather, before implementing personalised learning, we should progress thinking by investigating some of the primary challenges and how these challenges could result in a better understanding of young children's learning processes. Building on a workshop on the same theme during the 2020 Interaction Design for Children conference (Vanbecelaere et al., 2020), challenges were identified in four key areas: (1) the concept of technology‐mediated personalised learning; (2) the design of personalised technologies; (3) the evaluation methodologies exploring the effectiveness of personalised learning; and (4) the impact of technology‐mediated personalised learning on pedagogical practice, learning experiences and/or the teacher–learner relationship. This BJET special section sought to map out current research to address challenges in these four key areas to help move the debate forward and map out future directions for research.…”

Section: Moving the Debate Forwardmentioning

confidence: 99%

Technology‐mediated personalised learning for younger learners: Concepts, design, methods and practice

Vanbecelaere

Benton

2021

Brit J Educational Tech

Self Cite

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Children differ in various aspects such as prior knowledge, learning pace, socio-economic status, interests etc. It has been argued that when we take these differences into account when we develop learning environments, children will benefit from it in terms of learning outcomes, learning experience, and attitudes towards particular subjects. The emergence of digital technologies has accelerated the movement to create personalised learning environments. Although technology-mediated personalised learning is promising, several challenges remain such as how personalised learning should be conceptualized, which methods should be used to establish the effects and how this movement impacts education and especially children and teachers. This workshop aims to bring together researchers and practitioners who have done work in this field to facilitate in-depth discussions, resource exchange and networking on technologymediated personalised learning.

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Technology-mediated personalised learning for younger learners

Cited by 46 publications

References 19 publications

To use or not to use learning data: A survey study to explain German primary school teachers’ usage of data from digital learning platforms for purposes of individualization

To use or not to use learning data: A survey study to explain German primary school teachers’ usage of data from digital learning platforms for purposes of individualization

Algorithmic versus teacher‐led sequencing in a digital serious game and the development of second language reading fluency and accuracy

Technology‐mediated personalised learning for younger learners: Concepts, design, methods and practice

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