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Hayat Sahlaoui; El Arbi Abdellaoui Alaoui; Said Agoujil; Anand Nayyar – Education and Information Technologies, 2024
Predicting student performance using educational data is a significant area of machine learning research. However, class imbalance in datasets and the challenge of developing interpretable models can hinder accuracy. This study compares different variations of the Synthetic Minority Oversampling Technique (SMOTE) combined with classification…
Descriptors: Sampling, Classification, Algorithms, Prediction
Heilmann, John; Miller, Jon F. – Perspectives of the ASHA Special Interest Groups, 2023
Purpose: In the early 1980s, researchers and speech-language pathologists (SLPs) collaborated to develop the Systematic Analysis of Language Transcripts (SALT). Research and development over the ensuing decades has culminated into SALT Solutions, a set of tools to assist SLPs to efficiently complete language sample analysis (LSA) with their…
Descriptors: Sampling, Language Usage, Data Analysis, Data Collection
Sebahat Gok – ProQuest LLC, 2024
Many education researchers have advocated grounding abstract mathematical and scientific concepts in students' lived experiences, environmental interactions, and perceptions. This dissertation explores the causal effects of various grounding strategies in instructional settings, specifically on the topic of statistical sampling. The first chapter…
Descriptors: Teaching Methods, Attribution Theory, Statistics Education, Computer Simulation
Pavelko, Stacey L.; Owens, Robert E., Jr. – Perspectives of the ASHA Special Interest Groups, 2023
Purpose: The purposes of this tutorial are (a) to describe a method of language sample analysis (LSA) referred to as SUGAR (Sampling Utterances and Grammatical Analysis Revised) and (b) to offer step-by-step instructions detailing how to collect, transcribe, analyze, and interpret the results of a SUGAR language sample. Method: The tutorial begins…
Descriptors: Sampling, Language Tests, Data Collection, Data Analysis