Educational researchers often report effect sizes in standard deviation units (SD), but SD effects are hard to interpret. Effects are easier to interpret in percentile points, but converting SDs to percentile points involves a calculation that is not transparent to educational stakeholders. We show that if the outcome variable is normally…

With the increasingly prominent characteristics of data-intensive and AI-driven scientific paradigms, computing power has become a crucial pillar of research activities. This study aims to examine the knowledge innovation effects of university supercomputing development by theoretically proposing two mechanisms: the efficiency effect (including…

Prior research has suggested that clustered regression discontinuity designs are a formidable alternative to cluster randomized designs because they provide targeted treatment assignment while maintaining a high-quality basis for inferences on local treatment effects. However, methods for the design and analysis of clustered regression…

Nathalie Sinclair's MERGA 2024 keynote challenged us to communicate video data in ways that provide the reader with a more holistic and embodied experience of the data. In this methodological position paper, we take up this challenge. Through video analysis of a pre-school child and her mother engaging about counting in threes (prompted by the…

Computational Thinking (CT) is considered a core 21st century digital skill. The aspect of assessment is crucial and knowing what, who, when, how, and where to assess is important for assessment design. In this study, we conducted an umbrella review to gain insights regarding CT assessment in higher education. In total, we analyzed 11 reviews,…

Teaching coding and computational thinking is an emerging educational imperative, now embedded in compulsory curriculum in the United States, Finland, the UK, Germany, Belgium, the Netherlands, New Zealand, and Australia. This meta-synthesis of 49 studies critically reviews recent international research (2009-2022) of coding and computational…

Random encouragement designs evaluate treatments that aim to increase participation in a program or activity. These randomized controlled trials (RCTs) can also assess the mediated effects of participation itself on longer term outcomes using a complier average causal effect (CACE) estimation framework. This article considers power analysis…

Computational thinking is a relatively new field for teachers and educational researchers, where new pedagogical approaches emerge to teach various aspects of computational thinking that covers various thinking abilities and techniques for solving problems. Computational thinking concept received great attention from researchers and instructors…

Background and Context: Computational thinking (CT) has been increasingly added to K-12 curricula, prompting teachers to grade more and more CT artifacts. This has led to a rise in automated CT assessment tools. Objective: This study examines the scope and characteristics of publications that use machine learning (ML) approaches to assess…

The randomized control trial (RCT) is the primary experimental design in education research due to its strong internal validity for causal inference. However, in situations where RCTs are not feasible or ethical, quasi-experiments are alternatives to establish causal inference. This paper serves as an introduction to several quasi-experimental…

Multisite trials that randomize individuals (e.g., students) within sites (e.g., schools) or clusters (e.g., teachers/classrooms) within sites (e.g., schools) are commonly used for program evaluation because they provide opportunities to learn about treatment effects as well as their heterogeneity across sites and subgroups (defined by moderating…

This work aims to elaborate a governance composite index for research laboratories in public university. This index is composed by an indicator of responsible liberalism associating effectiveness and ethics, to which are added an organizational management indicator and a strategic management indicator. To achieve the above aim, several methods are…

The purpose of this paper is to explore three computational approaches to ethnographic research within digital learning environments: virtual ethnography; quantitative ethnography; and computational ethnography. Recently, researchers have become more interested in computational ethnographic approaches due to their alignment with the massive…

The federal government is the largest source of academic research and development (R&D) funding in the United States, providing funds through more than two dozen federal agencies. U.S. colleges and universities, often referred to as institutions of higher education (IHEs), play a role in the U.S. R&D ecosystem and in supporting American…

Computational thinking (CT) has been regarded as an essential skill set that students should acquire from their early years of life. As a thinking practice applicable to problem-solving processes, it has been argued that CT can be demonstrated and incorporated into other disciplines. While most studies have focused on CT integration with science,…