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Allison S. Theobold; Megan H. Wickstrom; Stacey A. Hancock – Journal of Statistics and Data Science Education, 2024
Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…
Descriptors: Computer Science Education, Coding, Data Science, Statistics Education
Nguyen, Ha; Parameswaran, Prasina – Information and Learning Sciences, 2023
Purpose: The goal of this study is to explore how content creators engage in critical data literacies on TikTok, a social media site that encourages the creation and dissemination of user-created, short-form videos. Critical data literacies encompass the ability to reason with, critique, control, and repurpose data for creative uses. Existing work…
Descriptors: Critical Literacy, Social Media, Video Technology, Criticism
Sefton-Green, Julian; Pangrazio, Luci – Educational Philosophy and Theory, 2022
Amidst ongoing technological and social change, this article explores the implications for critical education that result from a data-driven model of digital governance. The article argues that traditional notions of critique which rely upon the deconstruction and analysis of texts are increasingly redundant in the age of datafication, where the…
Descriptors: Data Analysis, Governance, Educational Philosophy, Barriers
Pillutla, Venkata Sai; Tawfik, Andrew A.; Giabbanelli, Philippe J. – Technology, Knowledge and Learning, 2020
In massive open online courses (MOOCs), learners can interact with each other using discussion boards. Automatically inferring the states or needs of learners from their posts is of interest to instructors, who are faced with a high attrition in MOOCs. Machine learning has previously been successfully used to identify states such as confusion or…
Descriptors: Learning Processes, Online Courses, Data Collection, Data Analysis
Cechinel, Cristian; Ochoa, Xavier; Lemos dos Santos, Henrique; Carvalho Nunes, João Batista; Rodés, Virginia; Marques Queiroga, Emanuel – British Journal of Educational Technology, 2020
The growth of Learning Analytics (LA) as a research field has been extensively documented since its beginnings. This paper provides a broad overview of the publications that Latin American authors have published in the last years by performing a quantitative review of the literature (from 2011 to 2019). A total of 282 papers were collected and…
Descriptors: Data Analysis, Authors, Foreign Countries, Ethics
Schermer, Maike; Fosker, Tim – International Journal of Research & Method in Education, 2020
Arguably one of the most valuable tools for investigating pupil behaviour in an educational environment is systematic classroom observation. Classroom observation is often cited as having the potential to enable research of the learning process in action. Low inference classroom observation instruments are designed to record a sequence of data…
Descriptors: Classroom Observation Techniques, Learning Processes, Intervals, Individual Differences
Zhang, Zheng; Nagle, Joelle; McKishnie, Bethany; Lin, Zhen; Li, Wanjing – Pedagogies: An International Journal, 2019
This systematic review is built on the seminal work by the New London Group in 1996. Few endeavours have synthesized findings of empirical studies pertaining to the effects and challenges of multiliteracies practices in various schooling and geographical contexts. Through a five-point Likert scale and a deductive and inductive thematic analysis,…
Descriptors: Multiple Literacies, Educational Research, Data Collection, Data Analysis
Hung, Jeng-Fung; Tsai, Chun-Yen – Journal of Baltic Science Education, 2020
Previous studies on the effectiveness of virtual laboratories for learning have shown inconsistent results over the past decade. The purpose of this research was to explore the effects of a virtual laboratory and meta-cognitive scaffolding on students' data modeling competences. A quasi-experimental design was used. Three classes of eighth graders…
Descriptors: Metacognition, Computer Simulation, Comparative Analysis, Science Laboratories
Ching, Cynthia Carter; Hagood, Danielle – Journal of Science Education and Technology, 2019
This paper connects the technological practice of activity monitor gaming to the Next Generation Science Standards (NGSS) science and engineering practice of "analyzing and interpreting data," and to the foundational constructionist idea of personal meaning. In our larger study, eighth-grade students, ages 12-14, wore physical activity…
Descriptors: Middle School Students, Grade 8, Educational Games, Academic Standards
Winne, Philip H.; Nesbit, John C.; Popowich, Fred – Technology, Knowledge and Learning, 2017
A bottleneck in gathering big data about learning is instrumentation designed to record data about processes students use to learn and information on which those processes operate. The software system nStudy fills this gap. nStudy is an extension to the Chrome web browser plus a server side database for logged trace data plus peripheral modules…
Descriptors: Data Collection, Research Methodology, Learning Processes, Computer Software
Chatti, Mohamed Amine; Muslim, Arham – International Review of Research in Open and Distributed Learning, 2019
Personalization is crucial for achieving smart learning environments in different lifelong learning contexts. There is a need to shift from one-size-fits-all systems to personalized learning environments that give control to the learners. Recently, learning analytics (LA) is opening up new opportunities for promoting personalization by providing…
Descriptors: Guidelines, Data Analysis, Learning Experience, Metacognition
Guo, Hongwen – ETS Research Report Series, 2017
Data collected from online learning and tutoring systems for individual students showed strong autocorrelation or dependence because of content connection, knowledge-based dependency, or persistence of learning behavior. When the response data show little dependence or negative autocorrelations for individual students, it is suspected that…
Descriptors: Data Collection, Electronic Learning, Intelligent Tutoring Systems, Information Utilization
Liu, Min; Lee, Jaejin; Kang, Jina; Liu, Sa – Technology, Knowledge and Learning, 2016
Using a multi-case approach, we examined students' behavior patterns in interacting with a serious game environment using the emerging technologies of learning analytics and data visualization in order to understand how the patterns may vary according to students' learning characteristics. The results confirmed some preliminary findings from our…
Descriptors: Case Studies, Student Behavior, Behavior Patterns, Games
Liu, Sanya; Hu, Zhenfan; Peng, Xian; Liu, Zhi; Cheng, H. N. H.; Sun, Jianwen – International Journal of Distance Education Technologies, 2017
In a MOOC environment, each student's interaction with the course content is a crucial clue for learning analytics, which offers an opportunity to record learner activity of unprecedented scale. In online learning, the educators and the administrators need to get informed with students' learning states since the performance of unsupervised…
Descriptors: Online Courses, Electronic Learning, Cognitive Style, Educational Research
New Data, Old Tensions: Big Data, Personalized Learning, and the Challenges of Progressive Education
Dishon, Gideon – Theory and Research in Education, 2017
Personalized learning has become the most notable application of big data in primary and secondary schools in the United States. The combination of big data and adaptive technological platforms is heralded as a revolution that could transform education, overcoming the outdated classroom model, and realizing the progressive vision of…
Descriptors: Data Collection, Data Analysis, Information Utilization, Individualized Instruction