Problem decomposition into sub-problems or subgoals and recomposition of the solutions to the subgoals into one complete solution is a common strategy to reduce difficulties in structured problem solving. In this study, we use a datadriven graph-mining-based method to decompose historical student solutions of logic-proof problems into Chunks. We…

Amidst ongoing technological and social change, this article explores the implications for critical education that result from a data-driven model of digital governance. The article argues that traditional notions of critique which rely upon the deconstruction and analysis of texts are increasingly redundant in the age of datafication, where the…

Background: Data literacy (DL) is vital for teachers, as it enables them to build on data and improve teaching and learning. Therefore, developing DL among pre-service teachers is critical. Objectives: The purpose of this study is threefold: to evaluate whether a feedback visualisation of peer assessment-based teaching approach (FVPA-based…

Ten years after the announcement of the "rise of the super experiment" at Educational Data Mining 2012, challenges to implementing "internet scale" educational experiments often persist for educational technology providers, especially when they seek to test substantive instructional interventions. Studies that deploy and test…

Background and Context: Assessing team members' indivdiual contributions to software development projects poses a key problem for computing instructors. While instructors typically rely on subjective assessments, objective assessments could provide a more robust picture. To explore this possibility, In a 2020 paper, Buffardi presented a…

This study examines the use of data analytics to evaluate students' behaviours during their participation in an online collaborative learning environment called SkyApp. To visualise the learning traits of engagement, emotion and motivation, students' inputs and activity data were captured and quantified for analysis. Experiments were first carried…

In this study, we examined the relationship between university students' engagement in a blended learning course and their performance. We also explored the roles which gender and nationality may play in the learning process. Our sample consisted of 335 students of International Accounting course. We used 23,796 student access computer logs as a…

Purpose: The paper aims to present a new two stage local causal learning algorithm -- HEISA. In the first stage, the algorithm discoveries the subset of features that better explains a target variable. During the second stage, computes the causal effect, using partial correlation, of each feature of the selected subset. Using this new algorithm,…

In Applied AI, or 'machine learning', methods such as neural networks are used to train computers to perform tasks without human intervention. In this article, we question the applicability of these methods to education. In particular, we consider a case of recent attempts from data scientists to add AI elements to a handful of online learning…

Though argumentation is a key component of scientific knowledge construction practices, it rarely occurs in classrooms worldwide. Moreover, related literature in the context of genetics and evolution learning primarily addresses them separately. In contrast, this paper is part of broader research on genetics and evolution instruction taught…

Since the publishing of Nolan and Temple Lang's "Computing in the Statistics Curriculum" in 2010, the American Statistical Association issued new recommendations in the revised GAISE college report. To reflect modern practice and technologies, they emphasize giving students experience with multivariable thinking. Students develop…

This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…

The influx of data and the advances in computing have led to calls to update the introductory statistics curriculum to better meet the needs of the contemporary workforce. To this end, we developed the COMputational Practices in Undergraduate TEaching of Statistics (COMPUTES) instrument, which can be used to measure the extent to which computation…

We describe an innovative preorientation curriculum (POC) for a Master of Biostatistics (MB) program. The goal of the POC is to fill critical skills gaps for students entering the MB program from heterogeneous backgrounds so they are prepared to engage in the program's rigorous, fast-paced training upon arrival. To achieve this goal, we introduce…

In secure web application development, the role of web services will not continue if it is not trustworthy. Retaining customers with applications is one of the major challenges if the services are not reliable and trustworthy. This article proposes a trust evaluation and decision model where the authors have defined indirect attribute, trust,…