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Ulitzsch, Esther; He, Qiwei; Pohl, Steffi – Journal of Educational and Behavioral Statistics, 2022
Interactive tasks designed to elicit real-life problem-solving behavior are rapidly becoming more widely used in educational assessment. Incorrect responses to such tasks can occur for a variety of different reasons such as low proficiency levels, low metacognitive strategies, or motivational issues. We demonstrate how behavioral patterns…
Descriptors: Behavior Patterns, Problem Solving, Failure, Adults
Jahnke, Maximilian; Höppner, Frank – International Educational Data Mining Society, 2022
The value of an instructor is that she exactly recognizes what the learner is struggling with and provides constructive feedback straight to the point. This work aims at a step towards this type of feedback in the context of an introductory programming course, where students perform program execution tracing to align their understanding of Java…
Descriptors: Programming, Coding, Computer Science Education, Error Patterns
Khor, Ean Teng – International Journal of Information and Learning Technology, 2022
Purpose: The purpose of the study is to build predictive models for early detection of low-performing students and examine the factors that influence massive open online courses students' performance. Design/methodology/approach: For the first step, the author performed exploratory data analysis to analyze the dataset. The process was then…
Descriptors: Prediction, Low Achievement, Algorithms, Artificial Intelligence
Kalkbrenner, Michael T. – Professional Counselor, 2022
Conducting and publishing rigorous empirical research based on original data is essential for advancing and sustaining high-quality counseling practice. The purpose of this article is to provide a one-stop-shop for writing a rigorous quantitative Methods section in counseling and related fields. The importance of judiciously planning,…
Descriptors: Guidelines, Statistical Analysis, Research Methodology, Counseling
Winne, Philip H. – Metacognition and Learning, 2022
Metacognition is the engine of self-regulated learning. At the object level, learners seek information and choose learning tactics and strategies they forecast will develop knowledge. At the meta level, learners gather and analyze data about learning events to draw conclusions, such as: Is this tactic a good fit to conditions? Was it effective?…
Descriptors: Metacognition, Learning Strategies, Computer Software, Data Analysis
Gao, Yizhu; Zhai, Xiaoming; Bulut, Okan; Cui, Ying; Sun, Xiaojian – Journal of Intelligence, 2022
This study investigated how one's problem-solving style impacts his/her problem-solving performance in technology-rich environments. Drawing upon experiential learning theory, we extracted two behavioral indicators (i.e., planning duration for problem solving and human-computer interaction frequency) to model problem-solving styles in…
Descriptors: Problem Solving, Cognitive Style, Technology Uses in Education, Adults
Yildirim-Tasti, Ozlem; Yildirim, Ali – Journal of Theoretical Educational Science, 2022
This paper aims to analyze the research literature on Turkish pre-service teachers' critical thinking skills (CTS) and critical thinking dispositions (CTD) to identify the major knowledge claims and areas of further research. This systematic review study examined both quantitative and qualitative studies conducted between years 2010-2020, in…
Descriptors: Preservice Teachers, Critical Thinking, Thinking Skills, Personality
Meyer, Brad C.; Bishop, Debra S. – Decision Sciences Journal of Innovative Education, 2022
This article examines how students learn about data-driven decision-making by creating and using a dashboard to play an online version of the familiar Beer Game. The objective is to apply data visualization skills to a business system in a way that leads to effective decisions. The students not only build a dashboard in Tableau, they also use it…
Descriptors: Visual Aids, Data Analysis, Decision Making, Computer Software
Shen, Jian; Luo, Qiang – Best Evidence in Chinese Education, 2022
The development of school education depends on the quality of the education provided, and it is a key metric for assessing the effectiveness of schools in developing talent. Building specialized, intelligent education quality monitoring (EQM) databases is crucial for speeding EQM progress in the big data era. This article examines the development…
Descriptors: Educational Quality, Quality Assurance, Databases, Foreign Countries
Region 8 Comprehensive Center, 2022
Most school and district leaders have a wealth of information available to them before, during, and after the hiring process, but they might not analyze it regularly or use it to inform their recruitment and retention plans. However, using data strategically is key to positively impacting teacher recruitment and retention. This brief discusses…
Descriptors: Data Use, Teacher Recruitment, Teacher Persistence, Elementary Secondary Education
Jonathan Seiden; Emily Hanno; Luke Miratrix; Thu Pham; Stephanie Jones; Nonie Lesaux – Society for Research on Educational Effectiveness, 2022
Background/Context: Quality in early education and care (ECE) programs is often conceived as a combination of structural features such as class size and teacher qualification and process features related to the interactions between and within children and adults in the care setting (Hanno et al., 2021; Howes et al., 2008). From a theoretical…
Descriptors: Educational Quality, Early Childhood Education, Outcomes of Education, Data Analysis
Ricardo J. Ferna´ndez-Tera´n; Estefani´a Sucre-Rosales; Lorenzo Echevarria; Florencio E. Hernández – Journal of Chemical Education, 2022
We present a detailed yet easy-to-follow discussion of the mathematical treatment of time-resolved spectroscopic data in a model-based approach. This is accompanied and complemented by an example of a colorful and pedagogically rich chemical reaction: the permanganate oxidation of sugars in basic aqueous media (often known as the chameleon…
Descriptors: Spectroscopy, Chemistry, Science Instruction, Mathematics
Keeanna Jessica Marie Warren – ProQuest LLC, 2022
Teacher turnover continues to be a significant problem in the United States. Teacher turnover is expensive because it costs money to continue recruiting, hiring, and training new teachers to replace those leaving (Carver-Thomas & Darling-Hammond, 2017). Most important though, teacher turnover hurts student achievement and success (Sorensen…
Descriptors: Data Analysis, Prediction, Teacher Persistence, Faculty Mobility
Anna G. Brady – Research in Science Education, 2024
Computer-based learning environments (CBLEs) are powerful tools to support student learning. Increasingly of interest is the data that is recorded as learners interact with a CBLE. This "process data" yields opportunities for researchers to examine learners' engagement with a CBLE and explore whether specific interactions are associated…
Descriptors: Electronic Learning, Educational Environment, Data Use, Learner Engagement
Christine Ye; Yuna Kim; Yoon-Na Cho – Journal of Marketing Education, 2024
Advances in digital technologies coupled with the explosion of data are transforming the marketing education landscape at a rapid pace. Given the scale and speed of digital disruption in today's industry, marketing academics face ongoing challenges of addressing the theory-practice gap, which will only accelerate. The purpose of the current study…
Descriptors: Business Administration Education, Internet, Marketing, Data Analysis