Machine learning methods can be used to reduce the manual workload in exam grading, making it possible for teachers to spend more time on other tasks. However, when it comes to grading exams, fully eliminating manual work is not yet possible even with very accurate automated grading, as any grading mistakes could have significant consequences for…

As universities shifted to online education with the onset of the Coronavirus Disease 2019 (COVID-19) pandemic, both pedagogy and assessment patterns across disciplines underwent a change, with a shift towards collaborative digital assessments. In this context, using qualitative and quantitative methods for data collection from an assessment…

This study proposes a software system for determining gaze patterns in on-screen testing. The system applies machine learning techniques to eye-movement data obtained from an eye-tracking device to categorize students according to their gaze behavior pattern while solving an on-screen test. These patterns are determined by converting eye movement…

E-learning plays a significant role in educating large number of students. In the delivery of e-learning material, automatic e-assessment has been applied only to some extent in the case of free response answers in highly technical diagrams in domains like software engineering, electronics, etc., where there is a great scope of imagination and…

This dissertation describes an experiment to investigate how learners with different levels of background in computer science learn core concepts of computer science, in particular, algorithms. We designed a study to focus on cognitive task analysis for eliciting the empirical mental elements of learning two graph algorithms. Cognitive workload…

We examine the effects of computer-based versus paper-based assessment of critical thinking skills, adapted from English (in the U.S.) to Chinese. Using data collected based on a random assignment between the two modes in multiple Chinese colleges, we investigate mode effects from multiple perspectives: mean scores, measurement precision, item…

This paper presents an innovative method to tackle the automatic evaluation of programming assignments with an approach based on well-founded assessment theories (Classical Test Theory (CTT) and Item Response Theory (IRT)) instead of heuristic assessment as in other systems. CTT and/or IRT are used to grade the results of different items of…

This research developed an approach to integrate the complementary benefits of digitized assessments and peer learning. Its basic premise and associated hypotheses are that by using student assessments of correct and incorrect quiz answers using a fine-grained resolution to pair them into remediation peer-learning cohorts is an effective means of…

During the last years online education, in particular Massive Open Online Courses (MOOCs), has contributed to spread and popularize educational methodologies such as peer-review, automatic assessment, self-paced courses, self-evaluation, etc. Although these techniques can benefit face-to-face courses, most of them are not yet widely used in these…

Information technology is now ubiquitous in higher education institutions worldwide. More than 85% of American universities use e-learning systems to supplement traditional classroom activities. An obvious benefit of these online tools is their ability to automatically grade exercises submitted by students and provide immediate feedback. Most of…

The main purpose of this study is to investigate the effects of integration of online learning and assessment in synchronization form (OLASF) on students' learning performance. The study seeks to evaluate how the synchronization content with immediate assessment can affect the knowledge performance of the students. An experimental design with…

When compared to earlier programming and data structure experiences that our students might have, the perspective changes on computers and programming when introducing theoretical computer science into the picture. Underlying computational models need to be addressed, and mathematical tools employed, to understand the quality criteria of…

In the study herein aimed at incorporating the entrepreneurship mindset early on in the engineering curriculum of undergraduate students via a final project of an introductory programming course with MATLAB. Students were asked to find a need on campus, in the society, or in the market with a business potential and write a standalone application…

Learning analytics offers insights into student behaviour and the potential to detect poor performers before they fail exams. If the activity is primarily online (for example computer programming), a wealth of low-level data can be made available that allows unprecedented accuracy in predicting which students will pass or fail. In this paper, we…

Computer aided assessment systems enable the collection of exact time and date information on students' activity on a course. These activity patterns reflect students' study habits and these study habits further predict students' likelihood to pass or fail a course. By identifying such patterns, those who design the courses can enforce positive…