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Khdir Ahmed Othman; Rebaz Anwar Omer; Abdalla Ali Amin Mohammad; Damir A. Safin – Journal of Chemical Education, 2024
Functional group analysis is an essential part of the curriculum for identifying unknown organic compounds. However, traditional methods of analyzing functional groups use excess reagents and generate a large amount of waste material that is difficult to dispose of. This work is focused on alternative methods for detecting functional groups such…
Descriptors: Organic Chemistry, Science Education, Scientific Concepts, Evaluation Methods
Irina Tursunkulova; Suzanne de Castell; Jennifer Jenson – International Association for Development of the Information Society, 2023
The exponential growth of scholarly publications in recent years has presented a daunting challenge for researchers to keep track of relevant articles within their research field. To address this issue, we examined the capabilities of InfraNodus, an AI-Powered text network analysis platform. InfraNodus promises to provide insights into any…
Descriptors: Research, Journal Articles, Artificial Intelligence, Evaluation Methods
Susan C. Mirabal; Darcy A. Reed; Yvonne Steinert; Cynthia R. Whitehead; Scott M. Wright; Sean Tackett – Advances in Health Sciences Education, 2024
While explicit conceptual models help to inform research, they are left out of much of the health professions education (HPE) literature. One reason may be the limited understanding about how to develop conceptual models with intention and rigor. Group concept mapping (GCM) is a mixed methods conceptualization approach that has been used to…
Descriptors: Allied Health Occupations Education, Medical Education, Concept Mapping, Learning Strategies
Tanja Kovacic; Cormac Forkan – Irish Educational Studies, 2024
Young people who are either at risk of disengaging or disengaged from mainstream education in Ireland are often supported by what is termed 'out-of-school' or the 'alternative education' sector. A recent review of out-of-school education provision (Department of Education. 2022. "Review of Out-of-School Educational Provision." Dublin:…
Descriptors: Foreign Countries, Nontraditional Education, Inclusion, Mainstreaming
Beena Joseph; Sajimon Abraham – Knowledge Management & E-Learning, 2023
Currently, the majority of e-learning lessons created and disseminated advocate a "one-size-fits-all" teaching philosophy. The e-learning environment, however, includes slow learners in a noticeable way, just like in traditional classroom settings. Learning analytics of educational data from a learning management system (LMS) have been…
Descriptors: Electronic Learning, Learning Management Systems, Slow Learners, Educational Environment
Cai, Zhiqiang; Li, Hiyiang; Hu, Xiangen; Graesser, Art – Grantee Submission, 2016
This paper provides an alternative way of document representation by treating topic probabilities as a vector representation for words and representing a document as a combination of the word vectors. A comparison on summary data shows that this representation is more effective in document classification. [This paper was published in:…
Descriptors: Probability, Natural Language Processing, Models, Automation
Smith, Charlie – Journal of Learning Spaces, 2017
For a number of years, higher education has moved away from didactic teaching toward collaborative and self-directed learning. This paper discusses how the configuration and spatial geometry of learning spaces influences engagement and interaction, with a particular focus on hierarchies between people within the space. Layouts, presented as…
Descriptors: Geometric Concepts, Space Utilization, Group Dynamics, Teacher Student Relationship
McNeish, Daniel M.; Stapleton, Laura M. – Educational Psychology Review, 2016
Multilevel models are an increasingly popular method to analyze data that originate from a clustered or hierarchical structure. To effectively utilize multilevel models, one must have an adequately large number of clusters; otherwise, some model parameters will be estimated with bias. The goals for this paper are to (1) raise awareness of the…
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Sample Size, Effect Size
Navarro, Richard; Barbarasa, Estera; Thakkar, Ami – RTI International, 2017
We explore the recent undertaking in El Salvador to establish the country's first industry-higher education clusters in four economic sectors critical to growth and competitiveness: (1) information and communication technology; (2) light manufacturing; (3) energy and energy efficiency; and (4) agroindustry and food processing. These clusters take…
Descriptors: Universities, College Role, Economic Development, Knowledge Economy
Xian, Sidong; Xia, Haibo; Yin, Yubo; Zhai, Zhansheng; Shang, Yan – Cogent Education, 2016
Teaching quality is the lifeline of the higher education. Many universities have made some effective achievement about evaluating the teaching quality. In this paper, we establish the Students' evaluation of teaching (SET) discriminant analysis model and algorithm based on principal component clustering analysis. Additionally, we classify the SET…
Descriptors: Discriminant Analysis, Factor Analysis, Student Evaluation of Teacher Performance, Instructional Effectiveness
Weber, Keith – North American Chapter of the International Group for the Psychology of Mathematics Education, 2014
Proof is a central concept in mathematics education, yet mathematics educators have failed to reach a consensus on how proof should be conceptualized. I advocate defining proof as a clustered concept, in the sense of Lakoff (1987). I contend that this offers a better account of mathematicians' practice with respect to proof than previous accounts…
Descriptors: Validity, Mathematical Logic, Mathematics Education, Mathematical Concepts
Wagler, Amy E. – Journal of Educational and Behavioral Statistics, 2014
Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for…
Descriptors: Hierarchical Linear Modeling, Cluster Grouping, Heterogeneous Grouping, Monte Carlo Methods
Ravinder, Handanhal; Misra, Ram B. – American Journal of Business Education, 2014
ABC analysis is a well-established categorization technique based on the Pareto Principle for determining which items should get priority in the management of a company's inventory. In discussing this topic, today's operations management and supply chain textbooks focus on dollar volume as the sole criterion for performing the categorization. The…
Descriptors: Facility Inventory, Evaluation Methods, Classification, Administration
Brint, Steven; Yoshikawa, Sarah R. K.; Rotondi, Matthew B.; Viggiano, Tiffany; Maldonado, John – Journal of Higher Education, 2016
Press reports and industry statistics both give incomplete pictures of the outcomes of the Great Recession for U.S. four-year colleges and universities. To address these gaps, we conducted a statistical analysis of all articles that appeared in Lexis-Nexis on a sample of more than 300 U.S. colleges and universities during the Recession years. We…
Descriptors: Colleges, Institutional Survival, Statistical Analysis, Literature Reviews
Timmermans, A. C.; de Wolf, I. F.; Bosker, R. J.; Doolaard, S. – Educational Assessment, Evaluation and Accountability, 2015
A recent development in educational accountability is a risk-based approach, in which intensity and frequency of school inspections vary across schools to make educational accountability more efficient and effective by enabling inspectorates to focus on organizations at risk. Characteristics relevant in predicting which schools are "at risk…
Descriptors: Accountability, Inspection, Underachievement, Achievement Gains