Short-Answer Grading (SAG) is a time-consuming task for teachers that automated SAG models have long promised to make easier. However, there are three challenges for their broad-scale adoption: A technical challenge regarding the need for high-quality models, which is exacerbated for languages with fewer resources than English; a usability…

Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…

Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…

This study investigates current approaches to learning analytics (LA) dashboarding while highlighting challenges faced by education providers in their operationalization. We analyze recent dashboards for their ability to provide actionable insights which promote informed responses by learners in making adjustments to their learning habits. Our…

Tasks for teaching predictive modelling and APIs often require learners to use code-driven tools. Minimal research, however, exists about the design of tasks that support the introduction of high school students and teachers to these new statistical and computational methods. Using a design-based research approach, a web-based task was developed.…

Self-report is a fundamental research tool for the social sciences. Despite quantitative surveys being the workhorses of the self-report stable, few researchers question their format--often blindly using some form of Labelled Categorical Scale (Likert-type). This study presents a brief review of the current literature examining the efficacy of…

Identifying at-risk students as soon as possible is a challenge in educational institutions. Decreasing the time lag between identification and real at-risk state may significantly reduce the risk of failure or disengage. In small courses, their identification is relatively easy, but it is impractical on larger ones. Current Learning Management…

Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…

The need to educate a competitive workforce is a global problem. In the US, for example, despite billions of dollars spent to improve the educational system, approximately 35% of students never finish high school. The drop rate among some demographic groups is as high as 50-60%. At the college level in the US only 30% of students graduate from…

A qualitative study was conducted to determine the perceptions of preservice teachers on how computers will be used in schools in the future. Undergraduate students (n=40) were given a 60-minute multimedia presentation on how computer and multimedia technologies are used in schools, followed by group discussions on the ways in which computers will…