Formative feedback is important in learning. Automating the provision of specific, objective, constructive feedback to large cohorts requires complex algorithms that most teachers do not have time to develop, suggesting that a community effort is needed to create a library of specialised algorithms. We present an exemplar algorithm for a class of…

The study presented in this paper uses heuristics from computer linguistics and graph theory to analyze a systematic literature review on educational technology. A literature review was conducted to validate an expert-based taxonomy which was developed to ontologize delivered teaching and learning for easy reuse. The sample includes N = 121…

We aimed to evaluate the performance of supervised machine learning algorithms in predicting articles relevant for full-text review in a systematic review. Overall, 16,430 manually screened titles/abstracts, including 861 references identified relevant for full-text review were used for the analysis. Of these, 40% (n = 6573) were sub-divided for…

In this article, we argue that automated scoring engines should be transparent and construct relevant--that is, as much as is currently feasible. Many current automated scoring engines cannot achieve high degrees of scoring accuracy without allowing in some features that may not be easily explained and understood and may not be obviously and…

Because the classification saves time in the learning process and enables this process to take place more easily, its contribution to music learning cannot be denied. One of the most valid and effective methods in music classification is music genre classification. Given the rapid progress of music production in the world and the significant…

Using a Dynamic Geometry System (DGS) students can engage in a dynamic learning process that allows them to experiment, create strategies, make conjectures, argue, and deduce mathematical properties. A DGS enables the introduction of proofs, by providing visual aids. The proof of the conjectures made emerges as the next step towards formalising…

As large-scale, sophisticated open and distance learning environments expand in higher education globally, so does the need to support learning at scale in real time. Valid, reliable rubrics of critical discourse are an essential foundation for developing artificial intelligence tools that automatically analyse learning in educator-student…

Despite a tremendous increase in the use of video for conducting research in classrooms as well as preparing and evaluating teachers, there remain notable challenges to using classroom videos at scale, including time and financial costs. Recent advances in artificial intelligence could make the process of analyzing, scoring, and cataloguing videos…

Automatic generation of math word problems (MWPs) is a challenging task in Natural Language Processing (NLP), particularly connecting it to real-life problems because it can benefit students in developing a higher level of mathematical thinking. However, most of the MWPs are presented within a scholastic setting in a decontextualized way. This…

Scoring essays is generally an exhausting and time-consuming task for teachers. Automated Essay Scoring (AES) facilitates the scoring process to be faster and more consistent. The most logical way to assess the performance of an automated scorer is by measuring the score agreement with the human raters. However, we provide empirical evidence that…

This paper presents a multidimensional model of variation in writing quality, register, and genre in student essays, trained and tested via confirmatory factor analysis of 1.37 million essay submissions to ETS' digital writing service, Criterion®. The model was also validated with several other corpora, which indicated that it provides a…

Existing approaches to measuring writing performance are insufficient in terms of both technical adequacy as well as feasibility for use as a screening measure. This study examined the validity and diagnostic accuracy of several approaches to automated text evaluation as well as written expression curriculum-based measurement (WE-CBM) to determine…

Existing approaches to measuring writing performance are insufficient in terms of both technical adequacy as well as feasibility for use as a screening measure. This study examined the validity and diagnostic accuracy of several approaches to automated text evaluation as well as written expression curriculum-based measurement (WE-CBM) to determine…

This case study explains the research procedures of a study that measured teachers' digital competency using a questionnaire and used an automated visualization platform to suggest appropriate professional development training based on their level of competency. To achieve the goal, the process was started by developing standard indicators for…

Classical automated test assembly (ATA) methods assume fixed and known coefficients for the constraints and the objective function. This hypothesis is not true for the estimates of item response theory parameters, which are crucial elements in test assembly classical models. To account for uncertainty in ATA, we propose a chance-constrained…