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Bostic, Jonathan David – Applied Measurement in Education, 2021
Think alouds are valuable tools for academicians, test developers, and practitioners as they provide a unique window into a respondent's thinking during an assessment. The purpose of this special issue is to highlight novel ways to use think alouds as a means to gather evidence about respondents' thinking. An intended outcome from this special…
Descriptors: Protocol Analysis, Cognitive Processes, Data Collection, STEM Education
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Wind, Stefanie A.; Ge, Yuan – Educational and Psychological Measurement, 2021
Practical constraints in rater-mediated assessments limit the availability of complete data. Instead, most scoring procedures include one or two ratings for each performance, with overlapping performances across raters or linking sets of multiple-choice items to facilitate model estimation. These incomplete scoring designs present challenges for…
Descriptors: Evaluators, Scoring, Data Collection, Design
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Crabtree, Gina; Wright, David – Strategic Enrollment Management Quarterly, 2021
Wichita State University (WSU) began the SEM process in 2015 with a steering committee co-chaired by the university registrar and the chief data officer (CDO). Work leading up to and undertaken throughout that process and the implementation of the SEM plan it produced helped to form an extraordinary partnership between these two professionals.…
Descriptors: Registrars (School), Institutional Research, Universities, Enrollment Management
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Yang, Chunsheng; Chiang, Feng-Kuang; Cheng, Qiangqiang; Ji, Jun – Journal of Educational Computing Research, 2021
Machine learning-based modeling technology has recently become a powerful technique and tool for developing models for explaining, predicting, and describing system/human behaviors. In developing intelligent education systems or technologies, some research has focused on applying unique machine learning algorithms to build the ad-hoc student…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Data Use, Models
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Ford, Karly S.; Rosinger, Kelly O.; Choi, Junghee; Pulido, Gabriel – Educational Researcher, 2021
Many postsecondary datasets collect gender data in ways that are not inclusive of all students. Many trans* students, those who identify as trans women, trans men, genderqueer, among other gender identities, are excluded when surveys collect gender data using only two categories. The American Bar Association recently became the first sector of…
Descriptors: Sexual Identity, LGBTQ People, Data Collection, College Students
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Perea Martins, J. E. M. – Physics Education, 2021
This work presents two electronic systems experiments with resonance tubes, which generate automatically a sequence of several sound wave frequencies in a range defined by the user and then verifies the amplitude of each one in real-time, allowing for the immediate data visualization in a graph. Besides, they save all the frequency values and the…
Descriptors: Design, Electronics, Laboratory Experiments, Acoustics
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Morgan, Lydia; Overton, Sarah; Bates, Sally; Titterington, Jill; Wren, Yvonne – International Journal of Language & Communication Disorders, 2021
Background: NHS case note data are a potential source of practice-based evidence which could be used to investigate the effectiveness of different interventions for individuals with a range of speech, language and communication needs. Consistency in pre- and post-intervention data as well as the collection of relevant variables would need to be…
Descriptors: Data Collection, Children, Intervention, Speech Impairments
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Atenas, Javiera; Havemann, Leo; Timmermann, Cristian – International Journal of Educational Technology in Higher Education, 2023
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…
Descriptors: Critical Literacy, Data Analysis, Ethics, Research Methodology
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Vallée, Etienne; Hsu, Yu-Chang – TechTrends: Linking Research and Practice to Improve Learning, 2023
The adoption by the African Union of its Convention on Cyber Security and Personal Data Protection in 2014 represented a step forward to protect personal data and to ensure that data remain private and secure. This is especially important for students, who often have no autonomy in the educational technology they use. Students cannot choose why…
Descriptors: Privacy, Information Security, Data Collection, Student Records
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Stewart, Bonnie E. – Contemporary Educational Technology, 2023
This paper is a critical case study tracing the professional history of a self-professed open educator over more than two decades. It frames the narrative of an individual as a window on the broader arc of the field, from early open learning as a means of widening participation, through the rise of the participatory web at scale, to the current…
Descriptors: Internet, Privacy, Open Education, Higher Education
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Rumary, Kevin James; Goldspink, Sally; Howlett, Philip – International Journal of Research & Method in Education, 2023
Data collection in qualitative research is intended to capture the participant experience in relation to defined phenomena. Whilst attention is given to the different ways of gathering qualitative data, the presence of the researcher is a common feature. However, the researcher does not hold an inert position in the data collection process and may…
Descriptors: Data Collection, Researchers, Focus Groups, Research Methodology
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Pols, Freek; Diepenbroek, Patrick – Physics Education, 2023
In practical work focussing on conceptual development, students spend valuable in-class time on collecting data rather than making sense out of it. This provides a barrier to learning about the targeted concept. To address this problem, we developed an approach that we coin "collaborative data collection." Using a practical on the topic…
Descriptors: Science Instruction, Concept Formation, Scientific Concepts, Data Collection
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Reeves Meyer, Justin; Heimlich, Joe E.; Horr, E. Elaine T.; Kemper, Rebecca F.; Börner, Katy – Journal of Museum Education, 2023
The article answers the research question: under what conditions and with what methods would museum visitors feel comfortable (and not comfortable) sharing sensitive information for the purposes of museum research or evaluation? We ground our study in literature about sharing personal information in person, online, and in the context of digital…
Descriptors: Museums, Informed Consent, Sharing Behavior, Information Dissemination
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Umer, Rahila; Susnjak, Teo; Mathrani, Anuradha; Suriadi, Lim – Interactive Learning Environments, 2023
Predictive models on students' academic performance can be built by using historical data for modelling students' learning behaviour. Such models can be employed in educational settings to determine how new students will perform and in predicting whether these students should be classed as at-risk of failing a course. Stakeholders can use…
Descriptors: Prediction, Student Behavior, Models, Academic Achievement
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Lee, Chia-An; Huang, Nen-Fu; Tzeng, Jian-Wei; Tsai, Pin-Han – IEEE Transactions on Learning Technologies, 2023
Massive open online courses offer a valuable platform for efficient and flexible learning. They can improve teaching and learning effectiveness by enabling the evaluation of learning behaviors and the collection of feedback from students. The knowledge map approach constitutes a suitable tool for evaluating and presenting students' learning…
Descriptors: Artificial Intelligence, MOOCs, Concept Mapping, Student Evaluation
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