This study investigated the effect of video lecture types on the performance of students in computational problem-solving practices. A total of 19 university students participated in the computational problem-solving practices that mostly required declarative knowledge, and 22 university students participated in the computational problem-solving…

The relationship between computational thinking (CT) and academic self-efficacy for building students' academic resilience--a trait crucial for problem-solving, peer relationships, and confidence development--was investigated. A mixed-methods approach was employed in a study involving 60 participants; half were given CT instruction and half were…

Background: Computational thinking (CT) is crucial to fostering critical thinking and problem-solving skills. Many elementary schools have been cultivating students' CT through block-based programming languages such as Scratch using traditional teacher-centered teaching methods. However, the approach excessively relies on teacher lectures, so the…

At present, the widespread use of online education platforms has attracted the attention of more and more people. The application of AI technology in online education platform makes multidimensional evaluation of students' ability become the trend of intelligent education in the future. Currently, most existing studies are based on traditional…

Artificial intelligence (AI) and computational sciences have aroused a growing interest in education. Despite its relatively recent history, AI is increasingly being introduced into the classroom through different modalities, with the aim of improving student achievement. Thus, the purpose of the research is to analyse, quantitatively and…

Educational data mining focuses on exploring increasingly large-scale data from educational settings, such as Learning Management Systems (LMS), and developing computational methods to understand students' behaviors and learning settings better. There has been a multitude of research dedicated to studying the student learning process, leading to…

This article proposes a flexible extension of the Fay--Herriot model for making inferences from coarsened, group-level achievement data, for example, school-level data consisting of numbers of students falling into various ordinal performance categories. The model builds on the heteroskedastic ordered probit (HETOP) framework advocated by Reardon,…

Model evaluation -- the process of making inferences about the performance of predictive models -- is a critical component of predictive modelling research in learning analytics. We survey the state of the practice with respect to model evaluation in learning analytics, which overwhelmingly uses only naïve methods for model evaluation or…

The majority of states include value-added models (VAMs) or some other measure of student academic growth as a component of their teacher evaluation systems. However, there is considerable disagreement among researchers about whether states and school districts should use student growth measures to make high-stakes personnel decisions. Many…

The current study investigated whether children's conformity to a majority testimony influenced their willingness to revise their own erroneous counting knowledge. The content of the testimonies focused on conventional rules of counting, by means of pseudoerrors (i.e., unconventional counts) occurring during a detection task. In this work…

Recently, there has been growing interest among practitioners and scientists in teaching children computer programming languages. The international efforts to raise generations who produce technologies are supported at the national level in Turkey too. Programming language education is included beginning from secondary school curricula of computer…

Background: Evaluating diversity, inclusivity, and equity remains both a prevalent topic in education and a difficult challenge for most evaluators. Traditional metrics used to evaluate these constructs include questionnaires, focus groups, and anonymous comment solicitations. While each of these approaches offer value, they also possess a number…

Curriculum-based measurement of oral reading (CBM-R) is used to index the level and rate of student growth across the academic year. The method is frequently used to set student goals and monitor student progress. This study examined the diagnostic accuracy and quality of growth estimates derived from pre-post measurement using CBM-R data. A…

Using an empirically-based simulation study, we show that typically used methods of choosing an item calibration sample have significant impacts on achievement bias and system rankings. We examine whether recent PISA accommodations, especially for lower performing participants, can mitigate some of this bias. Our findings indicate that standard…

This article provides a brief overview and comparison of three conditional growth percentile methods; student growth percentiles, percentile rank residuals, and a nonparametric matching method. These approaches seek to describe student growth in terms of the relative percentile ranking of a student in relationship to students that had the same…