Michael Mogessie

Carnegie Mellon University | CMU · Human-Computer Interaction Institute

Learning analytics research presents challenges for researchers embracing the principles of open science. Protecting student privacy is paramount, but progress in increasing scientific understanding and improving educational outcomes depends upon open, scalable and replicable research. Findings have repeatedly been shown to be contextually dependen...

Digital learning games are thought to support learning by increasing enjoyment and promoting deeper engagement with the content, but few studies have empirically tested hypothesized pathways between digital learning games and learning outcomes. Decimal Point, a digital learning game that teaches decimal operations and concepts to middle school stud...

Modern AIED systems develop sophisticated and multidimensional models of students. However, what is learned about students in one system-their skills, behaviors, and affect-is not carried over to other systems that could benefit students by using the information, potentially reducing both the effectiveness and efficiency of these systems. This chal...

Modern AIED systems develop sophisticated and multidimensional models of students. However, what is learned about students in one system—their skills, behaviors, and affect—is not carried over to other systems that could benefit students by using the information, potentially reducing both the effectiveness and efficiency of these systems. This chal...

Digital learning games are thought to support learning by increasing enjoyment and promoting deeper engagement with the content, but few studies have empirically tested hypothesized pathways between digital learning games and learning outcomes. Decimal Point, a digital learning game that teaches decimal operations and concepts to middle school stud...

Prior studies have explored the potential of erroneous examples in helping students learn more effectively by correcting errors in solutions to decimal problems. One recent study found that while students experience more confusion and frustration (confrustion) when working with erroneous examples, they demonstrate better retention of decimal concep...

Peer-assessment experiments were conducted among first and second year students at the University of Trento. The experiments spanned an entire semester and were conducted in five computer science courses between 2013 and 2016. Peer-assessment tasks included question and answer submission as well as answer evaluation tasks. The peer-assessment datas...

Confrustion, a mix of confusion and frustration sometimes experienced while grappling with instructional materials, is not necessarily detrimental to learning. Prior research has shown that studying erroneous examples can increase students’ experiences of confrustion, while at the same time helping them learn and overcome their misconceptions. In t...

Prior research suggests students can sometimes learn more effectively by explaining and correcting example problems that have been solved incorrectly, compared to problem-solving practice or studying correct solutions. It remains unclear, however, what role students' affect might play in the process of learning from erroneous examples. Specifically...

Predicting student success has long been an interest of institutions of higher education as well as organisations responsible for preparing high-stake, standardised tests administered at national and international levels. This study discusses how performance prediction studies have evolved from those that use demographic data and high school grades...

Peer-assessment in education has a long history. Although the adoption of technological tools is not a recent phenomenon, many peer-assessment studies are conducted in manual environments. Automating peer-assessment tasks improves the efficiency of the practice and provides opportunities for taking advantage of large amounts of student-generated da...

Predicting overall student performance and monitoring progress have attracted more attention in the past five years than before. Demographic data, high school grades and test result constitute much of the data used for building prediction models. This study demonstrates how data from a peer-assessment environment can be used to build student progre...

A common approach to the problem of predicting students’ exam scores has been to base this prediction on the previous educational history of students. In this paper, we present a model that bases this prediction on students’ performance on several tasks assigned throughout the duration of the course. In order to build our prediction model, we use d...

Peer assessment in higher education has been studied for decades. Despite the substantial amount of research carried out, peer assessment has yet to make significant advances. This review identifies themes of recent research and highlights the challenges that have hampered its advance. Most of these challenges arise from the manual nature of peer a...

One of the challenges of both traditional and contemporary instructional media in higher education is creating a sustainable teaching-learning environment that ensures continuous engagement of students and provides efficient means of assessing their performance. We present a peer-based framework designed to increase active participation of students...

We present an app that allows bringing video-lectures on Android devices in either a basic or a rich format. The paper also discusses in general terms the suitability of the video-lecture paradigm in a mobile setting.