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Caspari-Sadeghi, Sima – Cogent Education, 2023
Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication…
Descriptors: Learning Analytics, Data Analysis, Higher Education, Feedback (Response)
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Jingjing Long; Jiaxin Lin – Education and Information Technologies, 2024
English language learning students in China often feel challenged to learn English due to lack of motivation and confidence, pronunciation and grammar difference, lack of practice and people to communicate with etc., which affects students mental health. Adopting Big data and AI will help in overcoming these limitations as it provides personalized…
Descriptors: Foreign Countries, English Language Learners, College Students, Mental Health
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Kuntz, Emily M.; Massey, Cynthia C.; Peltier, Corey; Barczak, Mary; Crowson, H. Michael – Teacher Education and Special Education, 2023
Through time-series graphs, teachers often evaluate progress monitoring data to make both low- and high-stakes decisions for students. The construction of these graphs--specifically, the presence of an aimline and the data points per x- to y-axis ratio (DPPXYR)--may impact decisions teachers make. The purpose of this study was to evaluate the…
Descriptors: Graphs, Preservice Teachers, Accuracy, Decision Making
EdTrust-West, 2025
As California State University (CSU) launches its Pregnant and Parenting Students Initiative to increase graduation rates for parenting students at its campuses and works to implement the Greater Accessibility, Information, Notice, and Support (GAINS) for Student Parents Act, an exciting window of opportunity has opened for student voice to inform…
Descriptors: Child Rearing, Parents, College Students, Graduation Rate
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Esther Tenorio; Jimel Sandoval; Jenae Sanchez; Ryan Sanchez; Melina Salvador; Deborah B. Altschul – Health Education & Behavior, 2025
The Tribal-Academic partnership model described in this article uses Community-Based Participatory Research (CBPR) approaches to foster collaboration between community partners and academic researchers throughout study design, implementation, data collection, interpretation, and dissemination. Literature highlights the importance of community…
Descriptors: School Community Relationship, Research Design, Data Collection, Data Analysis
Sarah E. Long – ProQuest LLC, 2021
Missing values that fail to be appropriately accounted for may lead to reduced statistical power, biased estimators, reduced representativeness of the sample, and incorrect interpretations and conclusions (Gorelick, 2006). The current study provided an ontological perspective of data manipulation by explaining how statistical results can…
Descriptors: Statistics, Data Use, Student Records, School Holding Power
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Keith C. Radley; Evan H. Dart – Journal of Behavioral Education, 2025
Recent research has indicated that the manner in which single-case data are typically displayed for visual analysis may influence rater decisions regarding the effect of an intervention. Subsequently, researchers have encouraged adherence to a standard assembly for linear graphs in order to control these effects. Others, however, have encouraged…
Descriptors: Graphs, Research Design, Visual Aids, Data Analysis
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Ahn, June; Nguyen, Ha; Campos, Fabio – Contemporary Issues in Technology and Teacher Education (CITE Journal), 2021
In the United States, teachers are expected to analyze data to inform instruction and improve student learning. Despite investments in data tools, researchers find that teachers often interact with data visualizations in limited ways. Researchers have called for data interpretation training for preservice teachers to increase teachers'…
Descriptors: Visual Aids, Professional Autonomy, Data Interpretation, Data Use
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Gray, Cameron C.; Perkins, Dave; Ritsos, Panagiotis D. – Assessment & Evaluation in Higher Education, 2020
The field of learning analytics is progressing at a rapid rate. New tools, with ever-increasing number of features and a plethora of datasets that are increasingly utilized demonstrate the evolution and multifaceted nature of the field. In particular, the depth and scope of insight that can be gleaned from analysing related datasets can have a…
Descriptors: Educational Research, Data Collection, Data Analysis, Visual Aids
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Juliana Elisa Raffaghelli; Marc Romero Carbonell; Teresa Romeu-Fontanillas – Information and Learning Sciences, 2024
Purpose: It has been demonstrated that AI-powered, data-driven tools' usage is not universal, but deeply linked to socio-cultural contexts. The purpose of this paper is to display the need of adopting situated lenses, relating to specific personal and professional learning about data protection and privacy. Design/methodology/approach: The authors…
Descriptors: Artificial Intelligence, Data Collection, Information Literacy, Intervention
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Lucas Vasconcelos; Hengtao Tang; Ismahan Arslan-Ari; Michael M. Grant; Fatih Ari; Yingxiao Qian – Impacting Education: Journal on Transforming Professional Practice, 2024
Practitioner-focused educational doctoral programs have grown substantially in recent years. Dissertations in Practice (DiPs), which are the culminating research report and evaluation method in these programs, differ from traditional PhD dissertations in their focus on addressing a problem of practice and on connecting theories with practice. As…
Descriptors: Doctoral Programs, Online Courses, Asynchronous Communication, Doctoral Dissertations
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De Silva, Liyanachchi Mahesha Harshani; Chounta, Irene-Angelica; Rodríguez-Triana, María Jesús; Roa, Eric Roldan; Gramberg, Anna; Valk, Aune – Journal of Learning Analytics, 2022
Although the number of students in higher education institutions (HEIs) has increased over the past two decades, it is far from assured that all students will gain an academic degree. To that end, institutional analytics (IA) can offer insights to support strategic planning with the aim of reducing dropout and therefore of minimizing its negative…
Descriptors: College Students, Dropouts, Dropout Prevention, Data Analysis
Roger Sheng So – ProQuest LLC, 2024
Understanding student engagement with the institution from the first day of classes to the end of the semester would help inform the institution of the potential risk that a student will drop out of a class or of the school. Learning Management Systems (LMS) record student interactions with the system and might be able to be used to identify…
Descriptors: Learning Management Systems, Data Use, At Risk Students, Learner Engagement
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Petrescu, Claudia; Ellena, Adriano Mauro; Fernandes-Jesus, Maria; Marta, Elena – Youth & Society, 2022
Using the policy narrative framework, this article examines the pathways through which the development of policies (related to rural/small towns young NEETs in various EU countries) are based on evidence. To do this, we consider the Youth Guarantee (YG), an EU program (2014-2020) developed in several member countries with the aim of…
Descriptors: Out of School Youth, Unemployment, Public Policy, Foreign Countries
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Samudre, Mark D.; Allday, R. Allan; Lane, Justin D. – Education and Treatment of Children, 2022
The purpose of this study was to evaluate the use of behavioral skills training (BST) that included video vignettes used for modeling and rehearsal to train preservice general educators how to collect accurate antecedent-behavior-consequence (ABC) data using a structured recording format. The effectiveness of the intervention was evaluated within…
Descriptors: Preservice Teachers, Teacher Education, Data Collection, Student Behavior
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