Computational thinking (CT) is becoming increasingly important for K-12 science education, thus warranting new integrations of CT and science content. This intervention study integrated CT through unplugged, or handwritten, algorithmic explanations of natural selection. As students investigated natural selection in varying contexts (specific and…

The rapid integration of artificial intelligence (AI) into higher education has revolutionised academic research and teaching, offered transformative opportunities while raising significant ethical challenges. This Delphi study investigates the ethical dilemmas and institutional requirements for maintaining academic integrity in AI-driven…

School choice systems increasingly use common applications, where students can apply to multiple schools on a single form, though schools make admission decisions independently. We model three application systems: a common application, a decentralized system with costly separate applications, and a ranked-choice system using a matching algorithm.…

Background: Understanding algorithms is crucial for programming education, yet their abstract nature often challenges students. Algorithm visualisation (AV) has been proven effective in enhancing algorithmic thinking among university students. However, its efficacy for elementary school students and the optimal forms of AV tools remain unclear.…

Since 2018, institutions of higher education have been aware of the "enrollment cliff" which refers to expected declines in future enrollment. This paper attempts to describe how prepared institutions in Ohio are for this future by looking at trends leading up to the anticipated decline. Using IPEDS data from 2012-2022, we analyze trends…

Purpose: This study examined how physical education majors used computational thinking (CT) skills in a movement concept course. Method: Twenty-two physical education majors were tasked to create two gymnastics routines (i.e., algorithm design), analyze their routines (i.e., decomposition and abstraction), create and follow a personalized fitness…

The aim of this paper is to provide tools to teachers for monitoring student work and understanding practices in order to help student and possibly adapt exercises in the future. In the context of an online programming learning platform, we propose to study the attempts (i.e., submitted programs) of the students for each exercise by using…

This research works on creating a hybrid Knowledge Recommendation System (KRS) for an Entrepreneurship Course using the Knowledge Graph (KG) and Clustering Technologies (CTs). The system aims at improving students' learning experience by providing relevant learning materials and even focusing on learner preferences. These results are already part…

Open education systems play a significant role in providing flexible and accessible learning opportunities to large student populations, independent of time and location. These systems achieve cost efficiency through the effective implementation of economies of scale, reducing unit costs as student numbers increase. However, decision-making in the…

Collaborative learning in tertiary education faces challenges such as limited teacher intervention and effective student pairing. This study addresses these issues by proposing a data-driven peer recommendation approach enhanced with learner profile visualisation. The system dynamically matches students based on evolving learning profiles, using…

The main purpose of this research is to examine the informal strategies of fifth and sixth grade students while solving inverse proportional word problems. Multiple case study was used in this study. The research was carried out in a public middle school from a southern city of Türkiye. The participants of the research consist of three fifth and…

Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection programs that are accessible to R programmers: Google Cloud Vision, Amazon Rekognition, and…

Computer adaptive testing (CAT) is an increasingly common mode of test administration offering improved test security, better measurement precision, and the potential for shorter testing experiences. This article presents a new item selection algorithm based on a generalized objective function to support multiple types of testing conditions and…

Purpose: The Language ENvironment Analysis (LENA) technology uses automated speech processing (ASP) algorithms to estimate counts such as total adult words and child vocalizations, which helps understand children's early language environment. This ASP has been validated in North American English and other languages in predominantly monolingual…

The design of algorithms is one of the hardest topics of high school computer science. This is mainly due to the universality of algorithms as solution methods that guarantee the calculation of a correct solution for all potentially infinitely many instances of an algorithmic problem. The goal of this paper is to present a comprehensible and…