Billions of data in social media have provided a very influential platform for researchers to make research on data analysis. In the digital age, it has become essential for conducting an analysis of written things in social media in which the individuals express easily themselves without any pressure and for studying big data. It has been known…

In 2003, Holmes [The Statistician 52, Part 4, (2003), 439-474] reviewed 50 years of teaching statistics in English schools and drew out many lessons for more effective teaching. We consider the current relevance of several of these lessons and whether we have learned from them. Many national reports have been published about teaching statistics…

Real-time quantitative PCR is a technique used to monitor the PCR reaction in real time. RT-qPCR is broadly classified into two types based on its purpose: absolute and relative quantification. Absolute quantification is used in a wide array of fields such as microbiology, food technology, and biotechnology to quantify the microbiological…

We present a critical perspective on the current state of research on educational dialogues, within and without Computer-Supported Collaborative Learning environments, in order to propose research perspectives in the intersection of these two domains. Our main proposal is that in order to integrate different types of human or machine analyzed data…

Technical difficulties occasionally lead to missing item scores and hence to incomplete data on computerized tests. It is not straightforward to report scores to the examinees whose data are incomplete due to technical difficulties. Such reporting essentially involves imputation of missing scores. In this paper, a simulation study based on data…

Due to repeated observations of an outcome behavior in N-of-1 or single-case design (SCD) intervention studies, the occurrence of missing scores is inevitable in such studies. Approximately 21% of SCD articles published in five reputable journals between 2015 and 2019 exhibited evidence of missing scores. Missing rates varied by designs, with the…

A thematic evaluation of data journalism courses resulted in a typology that parses the field and offers guidance to educators. At the center is pattern detection, preceded by data acquisition and cleaning, and followed by data representation. The typology advances academic understanding by offering a precise conceptualization that distinguishes…

This paper explores the effect of using multitask learning for abstractive summarization in the context of small training corpora. In particular, we incorporate four different tasks (extractive summarization, language modeling, concept detection, and paraphrase detection) both individually and in combination, with the goal of enhancing the target…

Purpose: The purpose of this dissertation is to investigate the feasibility of using tests of robustness in peer review. This study involved selecting three high-impact papers which featured open data and utilized bioinformatic analyses but provided no source code and refactoring these to allow external survey participants to swap tools,…

Purpose: The datafication of teaching and learning settings continues to be of broad interest to the learning sciences. In response, this study aims to explore a non-traditional learning setting, specifically two Golf Teaching and Research Programs, to investigate how athletes and coaches capture, analyze and use performance data to improve their…

Machine Learning concept learns from experiences, inferences and conceives complex queries. Machine learning techniques can be used to develop the educational framework which understands the inputs from students, parents and with intelligence generates the result. The framework integrates the features of Machine Learning (ML), Explainable AI (XAI)…

This paper presents an ethical framework designed to support the development of critical data literacy for research methods courses and data training programmes in higher education. The framework we present draws upon our reviews of literature, course syllabi and existing frameworks on data ethics. For this research we reviewed 250 research…

Country differences in response styles (RS) may jeopardize cross-country comparability of Likert-type scales. When adjusting for rather than investigating RS is the primary goal, it seems advantageous to impose minimal assumptions on RS structures and leverage information from multiple scales for RS measurement. Using PISA 2015 background…

Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

Measurement uncertainty is a key topic in the university physics laboratory curriculum. In this study, we investigate students' ability to draw conclusions from measurement data and reasoning about measurement uncertainty in inquiry labs. This investigation centres around a task where students conclude whether measurements from two experiments…