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Taolin Zhang; Shuwen Jia; Charoula Angeli – International Journal of Web-Based Learning and Teaching Technologies, 2024
Considering the shortcomings of large evaluation errors, long time, human, and material resources in the evaluation process of the current college teaching mode to improve the accuracy of the evaluation of college teaching mode and reduce the cost of the evaluation, this study proposes an evaluation method for college teaching methods based on…
Descriptors: Evaluation Methods, Educational Change, Learning Analytics, Educational Technology
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Mark W. Isken – INFORMS Transactions on Education, 2025
A staple of many spreadsheet-based management science courses is the use of Excel for activities such as model building, sensitivity analysis, goal seeking, and Monte-Carlo simulation. What might those things look like if carried out using Python? We describe a teaching module in which Python is used to do typical Excel-based modeling and…
Descriptors: Spreadsheets, Models, Programming Languages, Monte Carlo Methods
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Nazanin Nezami; Parian Haghighat; Denisa Gándara; Hadis Anahideh – Grantee Submission, 2024
The education sector has been quick to recognize the power of predictive analytics to enhance student success rates. However, there are challenges to widespread adoption, including the lack of accessibility and the potential perpetuation of inequalities. These challenges present in different stages of modeling, including data preparation, model…
Descriptors: Evaluation Methods, College Students, Success, Predictor Variables
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Marcos Roque da Rosa; Clodis Boscarioli; Kátya Regina de Freitas Zara – International Journal of Sustainability in Higher Education, 2024
Purpose: This study aims to identify how literature has addressed sustainability reporting in universities over time and determine traceable patterns and trends. Design/methodology/approach: A comprehensive systematic review protocol of the Emerald Insight, Web of Science, Science Direct, Scopus, Springer Link and Wiley Online Library databases…
Descriptors: Sustainability, Universities, Institutional Evaluation, Reports
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Chavan, Pankaj; Mitra, Ritayan – Journal of Learning Analytics, 2022
The use of online video lectures in universities, primarily for content delivery and learning, is on the rise. Instructors' ability to recognize and understand student learning experiences with online video lectures, identify particularly difficult or disengaging content and thereby assess overall lecture quality can inform their instructional…
Descriptors: Learning Analytics, Video Technology, Lecture Method, Online Courses
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MacGregor, Stephen W.; Cooper, Amanda – AERA Online Paper Repository, 2022
We interrogate the opportunities and challenges of using mixed methods (MM) within a developmental evaluation (DE) context by drawing on two illustrative cases that investigated educational change in Canada. Methods: Multi-case design and cross-case analysis, with a focus on examining common patterns across the two cases, enabling new ways of…
Descriptors: Mixed Methods Research, Evaluation Methods, Barriers, Educational Change
Soubhik Barari; Eric Newsom; Ji Eun Park; Susan M. Paddock – NORC at the University of Chicago, 2024
Prospective students and their families use college rankings to navigate their higher education options. Rising tuition and fees have made the college decision more fraught. Recently, the major college ranking providers have revised their methodologies to reflect costs and other considerations. These revisions raise important questions about the…
Descriptors: Construct Validity, Evaluation Methods, Educational Quality, Student Costs
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Marjahan Begum; Pontus Haglund; Ari Korhonen; Violetta Lonati; Mattia Monga; Filip Strömbäck; Artturi Tilanterä – Informatics in Education, 2024
There can be many reasons why students fail to answer correctly to summative tests in advanced computer science courses: often the cause is a lack of prerequisites or misconceptions about topics presented in previous courses. One of the ITiCSE 2020 working groups investigated the possibility of designing assessments suitable for differentiating…
Descriptors: Foreign Countries, College Students, Prerequisites, Computer Science Education
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Yu Jie; Xinyun Zhou – International Journal of Web-Based Learning and Teaching Technologies, 2024
This paper explores using data mining in English teaching assessment in higher education within the 'Internet + Education' era. Traditional assessment methods struggle to meet modern teaching needs. By collecting diverse data like student performance and learning behavior, and employing data mining, a comprehensive assessment model is built. This…
Descriptors: College English, Program Evaluation, Evaluation Methods, Data Collection
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Gutiérrez-Mijares, María Eugenia; Josa, Irene; Casanovas-Rubio, Maria del Mar; Aguado, Antonio – Studies in Higher Education, 2023
Sustainability has increasingly become key in universities, as the objectives of sustainable development are essential to establish policies, guidelines and indicators that guide institutions to be more sustainable. This recognition has led many authors to develop methods to assess universities based on their performance in terms of sustainable…
Descriptors: Evaluation Methods, Sustainability, Higher Education, Educational Indicators
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Lomer, Sylvie; Mittelmeier, Jenna – Teaching in Higher Education, 2023
International students are a key demographic in UK higher education, yet there is limited literature dedicated to pedagogies for and with international students. We undertook a systematic literature review of journal articles from 2013 to 2019 which presented empirical evidence on specific pedagogic practices relating to international students in…
Descriptors: Foreign Students, Foreign Countries, Teaching Methods, Educational Research
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John N. Dyer – Journal of Instructional Pedagogies, 2023
Businesses and other organizations across the globe are becoming more and more data-driven, using a combination of descriptive, diagnostic, predictive and prescriptive analytics to gain a strategic advantage through understanding the past, what we hope to happen in the future, and the ability to accurately predict future outcomes. These forms of…
Descriptors: Data Analysis, Business, Business Administration Education, Information Literacy
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Leif Sundberg; Jonny Holmström – Journal of Information Systems Education, 2024
With recent advances in artificial intelligence (AI), machine learning (ML) has been identified as particularly useful for organizations seeking to create value from data. However, as ML is commonly associated with technical professions, such as computer science and engineering, incorporating training in the use of ML into non-technical…
Descriptors: Artificial Intelligence, Conventional Instruction, Data Collection, Models
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Matthew J. Mayhew; Christa E. Winkler – Journal of Postsecondary Student Success, 2024
Higher education professionals often are tasked with providing evidence to stakeholders that programs, services, and practices implemented on their campuses contribute to student success. Furthermore, in the absence of a solid base of evidence related to effective practices, higher education researchers and practitioners are left questioning what…
Descriptors: Higher Education, Educational Practices, Evidence Based Practice, Program Evaluation
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Watkins, Karen E.; Ellinger, Andrea D.; Suh, Boyung; Brenes-Dawsey, Joseph C.; Oliver, Lisa C. – European Journal of Training and Development, 2022
Purpose: The critical incident technique (CIT) is widely used in many disciplines; however, scholars have acknowledged challenges associated with analyzing qualitative data when using this technique. Therefore, the purpose of this article is to address the data analysis issues that have been raised by introducing some different contemporary ways…
Descriptors: Critical Incidents Method, Data Analysis, Doctoral Dissertations, Labor Force Development
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