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Johnson, Marina E.; Misra, Ram; Berenson, Mark – Decision Sciences Journal of Innovative Education, 2022
In the era of artificial intelligence (AI), big data (BD), and digital transformation (DT), analytics students should gain the ability to solve business problems by integrating various methods. This teaching brief illustrates how two such methods--Bayesian analysis and Markov chains--can be combined to enhance student learning using the Analytics…
Descriptors: Bayesian Statistics, Programming Languages, Artificial Intelligence, Data Analysis
Hoegh, Andrew – Journal of Statistics Education, 2020
While computing has become an important part of the statistics field, course offerings are still influenced by a legacy of mathematically centric thinking. Due to this legacy, Bayesian ideas are not required for undergraduate degrees and have largely been taught at the graduate level; however, with recent advances in software and emphasis on…
Descriptors: Bayesian Statistics, Statistics Education, Introductory Courses, Majors (Students)
Kubsch, Marcus; Stamer, Insa; Steiner, Mara; Neumann, Knut; Parchmann, Ilka – Practical Assessment, Research & Evaluation, 2021
In light of the replication crisis in psychology, null-hypothesis significance testing (NHST) and "p"-values have been heavily criticized and various alternatives have been proposed, ranging from slight modifications of the current paradigm to banning "p"-values from journals. Since the physics education research community…
Descriptors: Data Analysis, Bayesian Statistics, Educational Research, Science Education
Uwimpuhwe, Germaine; Singh, Akansha; Higgins, Steve; Coux, Mickael; Xiao, ZhiMin; Shkedy, Ziv; Kasim, Adetayo – Journal of Experimental Education, 2022
Educational stakeholders are keen to know the magnitude and importance of different interventions. However, the way evidence is communicated to support understanding of the effectiveness of an intervention is controversial. Typically studies in education have used the standardised mean difference as a measure of the impact of interventions. This…
Descriptors: Program Effectiveness, Intervention, Multivariate Analysis, Bayesian Statistics
Zhang, Zhidong – International Education Studies, 2016
This study explored an alternative assessment procedure to examine learning trajectories of matrix multiplication. It took rule-based analytical and cognitive task analysis methods specifically to break down operation rules for a given matrix multiplication. Based on the analysis results, a hierarchical Bayesian network, an assessment model,…
Descriptors: Alternative Assessment, Multiplication, Matrices, Learning
Hall, Stacey; Phang, Sen Han; Schaefer, Jeffrey P.; Ghali, William; Wright, Bruce; McLaughlin, Kevin – Advances in Health Sciences Education, 2014
Although the process of diagnosing invariably begins with a heuristic, we encourage our learners to support their diagnoses by analytical cognitive processes, such as Bayesian reasoning, in an attempt to mitigate the effects of heuristics on diagnosing. There are, however, limited data on the use ± impact of Bayesian reasoning on the accuracy of…
Descriptors: Computation, Probability, Pretests Posttests, Heuristics
Davidson, Lisa; Wilson, Colin – Second Language Research, 2016
Recent research has shown that speakers are sensitive to non-contrastive phonetic detail present in nonnative speech (e.g. Escudero et al. 2012; Wilson et al. 2014). Difficulties in interpreting and implementing unfamiliar phonetic variation can lead nonnative speakers to modify second language forms by vowel epenthesis and other changes. These…
Descriptors: Second Language Learning, Acoustics, Phonetics, Speech
Azevedo, Ana, Ed.; Azevedo, José, Ed. – IGI Global, 2019
E-assessments of students profoundly influence their motivation and play a key role in the educational process. Adapting assessment techniques to current technological advancements allows for effective pedagogical practices, learning processes, and student engagement. The "Handbook of Research on E-Assessment in Higher Education"…
Descriptors: Higher Education, Computer Assisted Testing, Multiple Choice Tests, Guides
Aslan, Burak Galip; Öztürk, Özlem; Inceoglu, Mustafa Murat – Educational Sciences: Theory and Practice, 2014
Considering the increasing importance of adaptive approaches in CALL systems, this study implemented a machine learning based student modeling middleware with Bayesian networks. The profiling approach of the student modeling system is based on Felder and Silverman's Learning Styles Model and Felder and Soloman's Index of Learning Styles…
Descriptors: Foreign Countries, Undergraduate Students, Graduate Students, Cognitive Style
Owen, Jesse; Thomas, LeKeldric; Rodolfa, Emil – Counseling Psychologist, 2013
The current study examined the associations among clients' perceptions of self- and social stigma for seeking help, session outcomes, and working alliance. Ninety-one clients were treated by 26 therapists, at a large university counseling center. All clients were currently in therapy. We expected that clients' perceptions of self- and social…
Descriptors: Self Concept, Social Bias, Correlation, Help Seeking
Pitchforth, Jegar; Beames, Stephanie; Thomas, Aleysha; Falk, Matthew; Farr, Charisse; Gasson, Susan; Thamrin, Sri Astuti; Mengersen, Kerrie – Journal of the Scholarship of Teaching and Learning, 2012
Completing a PhD on time is a complex process, influenced by many interacting factors. In this paper we take a Bayesian Network approach to analyzing the factors perceived to be important in achieving this aim. Focusing on a single research group in Mathematical Sciences, we develop a conceptual model to describe the factors considered to be…
Descriptors: Doctoral Degrees, Time to Degree, Bayesian Statistics, Network Analysis
Klugkist, Irene; van Wesel, Floryt; Bullens, Jessie – International Journal of Behavioral Development, 2011
Null hypothesis testing (NHT) is the most commonly used tool in empirical psychological research even though it has several known limitations. It is argued that since the hypotheses evaluated with NHT do not reflect the research-question or theory of the researchers, conclusions from NHT must be formulated with great modesty, that is, they cannot…
Descriptors: Psychological Studies, Hypothesis Testing, Researchers, Evaluation Methods
Hogarth, Robin M.; Soyer, Emre – Journal of Experimental Psychology: General, 2011
Recently, researchers have investigated differences in decision making based on description and experience. We address the issue of when experience-based judgments of probability are more accurate than are those based on description. If description is well understood ("transparent") and experience is misleading ("wicked"), it…
Descriptors: Foreign Countries, Graduate Students, College Students, Adults
Pullenayegum, Eleanor M.; Guo, Qing; Hopkins, Robert B. – Journal of Statistics Education, 2012
Graduate students in the health sciences who hope to become independent researchers must be able to write up their results at a standard suitable for submission to peer-reviewed journals. Bayesian analyses are still rare in the medical literature, and students are often unclear on what should be included in a manuscript. Whilst there are published…
Descriptors: Bayesian Statistics, Critical Thinking, Graduate Students, Health Sciences
Simonson, Michael, Ed. – Association for Educational Communications and Technology, 2015
For the thirty-eighth time, the Research and Theory Division of the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented at the annual AECT Convention in Indianapolis, Indiana. The Proceedings of AECT's Convention are published in two…
Descriptors: Information Technology, Educational Technology, Student Attitudes, Online Courses
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