Applying and Translating Learning Design and Analytics Approaches Across Borders

Rienties, Bart; Balaban, Igor; Divjak, Blaženka; Grabar, Darko; Svetec, Barbi; Vondra, Petra

doi:10.1007/978-3-031-27646-0_3

Cited by 3 publications

(3 citation statements)

References 34 publications

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“…There is some emerging literature on how Online Professional Development (OPD) can be used to connect educators across institutional and national borders (Bragg et al, 2021 ; Jayatilleke et al, 2017 ; Lantz-Andersson et al, 2018 ; Zhang et al, 2016 ) to help them to share and learn about innovative practice. There are several economic and social arguments why providing cross-institutional OPD might not only be financially attractive (Azzolini et al, 2022 ; Bragg et al, 2021 ; Rienties et al, 2013 ) but also might encourage sharing innovative practice beyond the borders of institutions and nations (Dennen & Bong, 2018 ; Lantz-Andersson et al, 2018 ; Macià & García, 2016 ; Rienties et al, 2023 ). At the same time, working together in different cultural and national OPD contexts might not always be straightforward (Dennen & Bong, 2018 ; Jayatilleke et al, 2017 ; Martin et al, 2019 ), and local/national educational policies might impose country-specific requirements in terms of which educational goals need to be covered.…”

Section: Discussionmentioning

confidence: 99%

“…Working together in smaller self-selected groups participants developed a (fictive) joined learning design in an innovative interactive tool called Balanced Design Planning (BDP: Divjak et al, 2022a ; Rienties et al, 2023 )). The expectation was that the learning design should at least include some element of FC or WBL.…”

Section: Methodsmentioning

confidence: 99%

“…The closed items focussed on the lived experiences of the design of the e-course (11 items, α = 0.889, e.g., “The materials, articles, and case-studies provided were useful for my learning”, “I enjoyed working with colleagues in this course”), the technology-acceptance of the BDP tool in particular (4 items α = 0.770, e.g., “I find it easy to get the BDP tool to do what I want it to do”), and the (potential) impact of the e-course on educators’ practice (8 items α = 0.874, e.g., “The course has encouraged me to use innovative teaching methods”). These three constructs were designed on purpose by the project team of Project XYZ based upon the above literature and research on learning design (Divjak et al, 2022a ; Rienties et al, 2023 ). In total 79 educators completed this survey, of which 68 Croatian, German, and UK educators were included.…”

Section: Methodsmentioning

confidence: 99%

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Online professional development across institutions and borders

Rienties

Divjak

Eichhorn

et al. 2023

Int J Educ Technol High Educ

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Professional development (PD) is a key element for enhancing the quality of academic teaching. An increasing number of PD activities have moved to blended and online formats, especially since the COVID-19 pandemic. Due to the desire, potential, and need for collaboration among educators to learn from innovative and best practices, several institutions have started to pool their resources and expertise together and have started to implement cross-institutional and cross-national online professional development (OPD). The questions of what type of a (cross-)institutional OPD educators might prefer, and whether educators learn effectively from (and with) peers in such cross-cultural context have not been adequately explored empirically. In this case-study across three European countries, we explored the lived experiences of 86 educators as a result of a cross-institutional OPD. Using a mixed methods design approach our pre-post findings indicated that, on average, participants made substantial gains in knowledge. In addition, several cultural differences were evident in the expectations and lived experiences in ODP, as well as the intention to transfer what had been learned into one's own practice of action. This study indicates that while substantial economic and pedagogical affordances are provided with cross-institutional OPD, cultural differences in context might impact the extent to which educators implement lessons learned from OPD.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Online professional development across institutions and borders

Rienties

Divjak

Eichhorn

et al. 2023

Int J Educ Technol High Educ

Self Cite

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How can valid and reliable automatic formative assessment predict the acquisition of learning outcomes?

Divjak,

Svetec,

Horvat

2024

Computer Assisted Learning

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BackgroundSound learning design should be based on the constructive alignment of intended learning outcomes (LOs), teaching and learning activities and formative and summative assessment. Assessment validity strongly relies on its alignment with LOs. Valid and reliable formative assessment can be analysed as a predictor of students' academic performance, but the question is how significant its predictive power is, and what other elements can affect predictions.ObjectivesOur aim was to investigate the predictive power of formative assessment for summative assessment, measuring the acquisition of LOs.MethodsWe analysed formative assessment results (quizzes, homework), together with log data (video and other material use, class attendance), to determine the most influential predictors and establish a reliable predictive learning analytics model. We used the Random Forest algorithm. The model is based on the data from two university mathematical courses, delivered at different years and levels of study, incorporating 813 students in two consecutive years.Results and ConclusionsOur results show that formative assessment, together with previous summative assessment, is a stronger predictor of summative assessment results than other data on students' engagement. The study pointed to the importance of completeness and quality of data, and clear links between assessment and LOs when making predictions of student results. It suggested that predictions are less reliable for the lowest and the highest performing students. It was noted that other factors can also affect predictions, like the level of LOs, or factors not easily extracted from digital data, like the learning environment and individual students' strategies.

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