scholarly journals Policy Document on Evaluation of Student Outcomes, Program Intended Learning Outcomes and Faculty Loading in Higher Quality Accredited Institutions

2018 ◽  
Author(s):  
Christo Ananth
Keyword(s):  
Learning Outcomes ◽  
Student Outcomes ◽  
Policy Document ◽  
Accredited Institutions ◽  
Intended Learning Outcomes

scholarly journals Predicting Student Performance Using Data Mining and Learning Analytics Techniques: A Systematic Literature Review

2020 ◽  
Vol 11 (1) ◽  
pp. 237
Author(s):  
Abdallah Namoun ◽  
Abdullah Alshanqiti
Keyword(s):  
Academic Success ◽  
Student Learning ◽  
Learning Outcomes ◽  
Student Performance ◽  
Student Outcomes ◽  
Predictive Analytics ◽  
Research Work ◽  
Supervised Machine Learning ◽  
Bibliographic Databases ◽  
Learning And Teaching

The prediction of student academic performance has drawn considerable attention in education. However, although the learning outcomes are believed to improve learning and teaching, prognosticating the attainment of student outcomes remains underexplored. A decade of research work conducted between 2010 and November 2020 was surveyed to present a fundamental understanding of the intelligent techniques used for the prediction of student performance, where academic success is strictly measured using student learning outcomes. The electronic bibliographic databases searched include ACM, IEEE Xplore, Google Scholar, Science Direct, Scopus, Springer, and Web of Science. Eventually, we synthesized and analyzed a total of 62 relevant papers with a focus on three perspectives, (1) the forms in which the learning outcomes are predicted, (2) the predictive analytics models developed to forecast student learning, and (3) the dominant factors impacting student outcomes. The best practices for conducting systematic literature reviews, e.g., PICO and PRISMA, were applied to synthesize and report the main results. The attainment of learning outcomes was measured mainly as performance class standings (i.e., ranks) and achievement scores (i.e., grades). Regression and supervised machine learning models were frequently employed to classify student performance. Finally, student online learning activities, term assessment grades, and student academic emotions were the most evident predictors of learning outcomes. We conclude the survey by highlighting some major research challenges and suggesting a summary of significant recommendations to motivate future works in this field.

Impacts of Experiential Learning Depth and Breadth on Student Outcomes

2016 ◽  
Vol 40 (1) ◽  
pp. 5-23 ◽  
Author(s):  
Jeffrey Scott Coker ◽  
Evan Heiser ◽  
Laura Taylor ◽  
Connie Book
Keyword(s):  
Experiential Learning ◽  
General Education ◽  
Learning Outcomes ◽  
Student Outcomes ◽  
Undergraduate Research ◽  
Higher Order Thinking ◽  
Senior Year ◽  
Time Commitment ◽  
Leadership Experiences ◽  
Different Types

This 5-year study of graduating seniors at Elon University ( n = 2,058) evaluates the impacts of experiential learning depth (amount of time commitment) and breadth (number of different types of experiences) on student outcomes. Data on study abroad, undergraduate research, internships, service, and leadership experiences were pulled from cocurricular transcripts and paired with responses to the National Survey of Student Engagement. Both depth and breadth were associated with acquiring a broad general education, writing clearly and effectively, contributing to the welfare of communities, relationships with faculty and administration, and desire to attend the same institution. Depth (but not breadth) was associated with higher order thinking (synthesis and application) in the senior year, as well as overall educational experience. Breadth (but not depth) was associated with working effectively with others and better relationships with other students. Overall, key learning outcomes desired for a college student are driven by both experiential learning depth and breadth.

Intelligent Agent-Based e-Learning System for Adaptive Learning

2012 ◽  
pp. 145-158
Author(s):  
Hokyin Lai ◽  
Minhong Wang ◽  
Huaiqing Wang
Keyword(s):  
Individual Differences ◽  
Learning Outcomes ◽  
Adaptive Learning ◽  
Main Idea ◽  
Learning Approaches ◽  
E Learning ◽  
Treatment Interaction ◽  
Multi Agent ◽  
The Individual ◽  
Intended Learning Outcomes

Adaptive learning approaches support learners to achieve the intended learning outcomes through a personalized way. Previous studies mistakenly treat adaptive e-Learning as personalizing the presentation style of the learning materials, which is not completely correct. The main idea of adaptive learning is to personalize the earning content in a way that can cope with individual differences in aptitude. In this study, an adaptive learning model is designed based on the Aptitude-Treatment Interaction theory and Constructive Alignment Model. The model aims at improving students’ learning outcomes through enhancing their intrinsic motivation to learn. This model is operationalized with a multi-agent framework and is validated under a controlled laboratory setting. The result is quite promising. The individual differences of students, especially in the experimental group, have been narrowed significantly. Students who have difficulties in learning show significant improvement after the test. However, the longitudinal effect of this model is not tested in this study and will be studied in the future.

Building the Entrepreneurial Mindset Through Cross-Functional Innovation Teams

2019 ◽  
Vol 3 (1) ◽  
pp. 41-59 ◽  
Author(s):  
Mary Schoonmaker ◽  
Robert Gettens ◽  
Glenn Vallee
Keyword(s):  
Learning Outcomes ◽  
Student Outcomes ◽  
Engineering Students ◽  
Assessment Tool ◽  
Student Learning Outcomes ◽  
Engineering Student ◽  
Course Assessment ◽  
Course Changes ◽  
Functional Teams ◽  
Development Course

This learning innovation article’s purpose is to provide educators with a course assessment tool that can be used to improve student outcomes in an undergraduate, production innovation, and development course, comprised of cross-functional teams (business and engineering students). We demonstrate how over a period of three years, we used the assessment tool to help make course changes that would influence student learning outcomes. In addition, we illustrate how the tool helped us to focus on particular student skills, make specific changes targeted at selected skills, and measure if these course changes were effective with engineering student outcomes.

Sign in / Sign up

Export Citation Format

Share Document