Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 2 |
| Since 2016 (last 10 years) | 6 |
| Since 2006 (last 20 years) | 6 |
Descriptor
Source
| Journal of Statistics and… | 2 |
| International Educational… | 1 |
| International Review of… | 1 |
| Journal of Educational… | 1 |
| Journal of Educational… | 1 |
Author
| Baker, Catherine M. | 1 |
| D'Souza, Daryl | 1 |
| Gasper, Rebecca E. | 1 |
| Hew, Khe Foon | 1 |
| Laakso, Mikko-Jussi | 1 |
| Lin, Guan-Yu | 1 |
| Qiao, Chen | 1 |
| Reilly, Joseph M. | 1 |
| Schneider, Bertrand | 1 |
| Schwab-McCoy, Aimee | 1 |
| Tang, Ying | 1 |
| More ▼ | |
Publication Type
| Reports - Research | 6 |
| Journal Articles | 5 |
| Speeches/Meeting Papers | 1 |
Education Level
| Higher Education | 6 |
| Postsecondary Education | 5 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
| Motivated Strategies for… | 1 |
What Works Clearinghouse Rating
Peer reviewed
Direct linkVance, Eric A. – Journal of Statistics and Data Science Education, 2021
Data science is collaborative and its students should learn teamwork and collaboration. Yet it can be a challenge to fit the teaching of such skills into the data science curriculum. Team-Based Learning (TBL) is a pedagogical strategy that can help educators teach data science better by flipping the classroom to employ small-group collaborative…
Descriptors: Cooperative Learning, Data Analysis, Statistics Education, Flipped Classroom
Schwab-McCoy, Aimee; Baker, Catherine M.; Gasper, Rebecca E. – Journal of Statistics and Data Science Education, 2021
In the past 10 years, new data science courses and programs have proliferated at the collegiate level. As faculty and administrators enter the race to provide data science training and attract new students, the road map for teaching data science remains elusive. In 2019, 69 college and university faculty teaching data science courses and…
Descriptors: Statistics Education, Higher Education, College Students, Teaching Methods
Download full textHew, Khe Foon; Qiao, Chen; Tang, Ying – International Review of Research in Open and Distributed Learning, 2018
Although massive open online courses (MOOCs) have attracted much worldwide attention, scholars still understand little about the specific elements that students find engaging in these large open courses. This study offers a new original contribution by using a machine learning classifier to analyze 24,612 reflective sentences posted by 5,884…
Descriptors: Learner Engagement, Large Group Instruction, Online Courses, Man Machine Systems
Reilly, Joseph M.; Schneider, Bertrand – International Educational Data Mining Society, 2019
Collaborative problem solving in computer-supported environments is of critical importance to the modern workforce. Coworkers or collaborators must be able to co-create and navigate a shared problem space using discourse and non-verbal cues. Analyzing this discourse can give insights into how consensus is reached and can estimate the depth of…
Descriptors: Problem Solving, Discourse Analysis, Cooperative Learning, Computer Assisted Instruction
Lin, Guan-Yu – Journal of Educational Computing Research, 2016
This study has two central purposes: First, it examines not only the roles of gender and persistence in undergraduate computing majors' learning self-efficacy, computer self-efficacy, and programming self-efficacy but also Bandura's hypothesized sources of self-efficacy; second, it examines the influence of sources of efficacy on the three…
Descriptors: Sex Role, Persistence, Self Efficacy, Beliefs
Veerasamy, Ashok Kumar; D'Souza, Daryl; Laakso, Mikko-Jussi – Journal of Educational Technology Systems, 2016
This article presents a study aimed at examining the novice student answers in an introductory programming final e-exam to identify misconceptions and types of errors. Our study used the Delphi concept inventory to identify student misconceptions and skill, rule, and knowledge-based errors approach to identify the types of errors made by novices…
Descriptors: Computer Science Education, Programming, Novices, Misconceptions
