The Jeong (2020) study found that greater use of backward and depth-first processing was associated with higher scores on students' argument maps and that analysis of only the first five nodes students placed in their maps predicted map scores. This study utilized the jMAP tool and algorithms developed in the Jeong (2020) study to determine if the…

In an Intelligent Tutoring System (ITS), problem (or question) difficulty is one of the most critical parameters, directly impacting problem design, test paper organization, result analysis, and even the fairness guarantee. However, it is very difficult to evaluate the problem difficulty by organized pre-tests or by expertise, because these…

Accounting for complex interactions between contextual variables and learners' individual differences in aptitudes and background requires building the means to connect and access learner data at large scales, across time, and in multiple contexts. This paper describes the ASU Learning@Scale (L@S) project to develop a digital learning network…

Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…

A major criticism brought to digital learning environments was that the individual learning activities cannot be monitored consistently. However, recent advancements of educational data mining and learning analytics allow a precise tracking of learner activities. Previous studies focused on learners' navigation profiles, academic achievements, or…

A significant amount of research has gone into predicting student performance and many studies have been conducted to predict why students drop out. A variety of data including digital footprints, socio-economic data, financial data, and psychological aspects have been used to predict student performance at the test, course, or program level.…

E-tutorial learning aids as worked examples and hints have been established as effective instructional formats in problem-solving practices. However, less is known about variations in the use of learning aids across individuals at different stages in their learning process in student-centred learning contexts. This study investigates different…

Grade prediction for future courses not yet taken by students is important as it can help them and their advisers during the process of course selection as well as for designing personalized degree plans and modifying them based on their performance. One of the successful approaches for accurately predicting a student's grades in future courses is…

Student grade prediction is a popular task for learning analytics, given grades are the traditional form of student performance. However, no matter the learning environment, student background, or domain content, there are things in common across most experiences in learning. In most previous machine learning models, previous grades are considered…

Early predictors of student success are becoming a key tool in flipped and online courses to ensure that no student is left behind along course activities. However, with an increased interest in this area, it has become hard to keep track of what the state of the art in early success prediction is. Moreover, prior work on early success prediction…

Writing is a challenge and a potential obstacle for students in U.S. 4-year postsecondary institutions lacking prerequisite writing skills. This study aims to address the research question: Is there a relationship between specific features (analytics) in coursework writing and broader success predictors? Knowledge about this relationship could…

The search for rigor in learning analytics applications has placed survey data in the suspect's corner, favoring more objective trace data. A potential lack of objectivity in survey data is the existence of response styles, the tendency of respondents to answer survey items in a particular biased manner, such as yeah saying or always disagreeing.…

To understand how learner metacognition and goal orientation affect learner problem-solving in a Serious Game (SG) environment, this study examined 12 undergraduate students' metacognition, goal orientations, and problem-solving performances and processes while playing a SG that adopts problem-based learning pedagogy to teach space science.…

Academic grades in assessments are predicted to determine if a student is at risk of failing a course. Sequential models or graph neural networks that have been employed for grade prediction do not consider relationships between course descriptions. We propose the use of text mining to extract semantic, syntactic, and frequency-based features from…

Open Online Courses can serve different purposes: in the case of Orient@mente at the University of Torino, they aim at facilitating the transition from secondary to tertiary education with automatic evaluation tests that students can try in order to understand their capabilities in - and their attitude towards - certain disciplines, and with…