Conditional Release Technologies for Management Education

Award Winner: 
2013 Sloan-C Effective Practice Award
Author Information
Author(s): 
Owen P. Hall, Jr.
Institution(s) or Organization(s) Where EP Occurred: 
Pepperdine University - Graziadio School of Business and Management
Effective Practice Abstract/Summary
Abstract/Summary of Effective Practice: 

Learning management systems (LMS) have come a long way since Sir Isaac Pitman initiated the first correspondence course in the early 1840s. Today, the demands of globalization call for new and innovative learning systems for enhancing management education. One approach for meeting these challenges is through the increased use of conditional release technologies (CRT) via LMS. The primary aim of CRTs is to distribute knowledge in small and more management learning packages based on student performance and characteristics. Intelligent tutors provide the vehicle for helping identify the appropriate material. CRTs have been used by the author in a variety of management education courses with continued success. CRTs have been found to be particularly useful in the growing online learning community.

Description of the Effective Practice
Description of the Effective Practice: 

Conditional release technologies (CRT) represent a key feature of any effective learning assurance effort. CRT can be defined as systems that release content based on student performance and characteristics. As it is generally recognized that students entering a program of management education possess a wide range of experiences and capabilities, CRT allows customization of content based upon such differences. One of the advantages of CRT is that it provides a flexible learning platform that can be customized to meet the needs of a wide portfolio of management education programs. For a CRT to operate independently according to the needs of the learners requires a responsive system that can assess student performance and respond accordingly. This functionality is provided by intelligent tutors. These systems offer the capability to assist students in overcoming specific technical challenges by assessing their performance and providing customized content. The CRT system used in this application is based on Delone's e-learning success model. This paradigm suggests that content must enhance learning and support learning goals and should never distract and/or detract from the learning process. Specific benefits of CRT for management education include:

• Delivers customized content at a time and place convenient to the student
• Affords the student with an integrated perspective on the course/program
• Presents rich instructional content including real-time feedback
• Offers courses designed for specific learning applications
• Increases opportunities for student and team participation and interaction
• Improves quality through learning assurance
• Provides direct linkage with Internet and library resources

Supporting Information for this Effective Practice
Evidence of Effectiveness: 

A review of the relevant literature (see below) suggests the conditional release technologies are at the leading edge of online educational programs. Conditional release technologies offer students a wide variety of learning opportunities based on customized content. The current system can identify and deliver specific content based on student performance and characteristics. Recent data on the use of conditional release technologies found: 1)Students consistently recognized that video lectures provided the highest degree of choice and control since students could choose which portions to watch at any time of their choosing, 2) Students found themselves generally more engaged in the tutorials that gave them the highest level of bandwidth and engagement without technological interference or latency and 3) Students noted that on-line quizzes were the most challenging activity; this is not an unexpected finding given the lack of control, i.e., the students had a relatively fixed amount of time and were constrained to a fixed date and time. The current system now makes it possible to provide educational opportunities to those students that are either without the traditional infrastructure or that are physically dispersed which is the hallmark of an online program.

How does this practice relate to pillars?: 

The use of conditional release technologies supports both student learning effectiveness and satisfaction. Student performance and survey response data indicates widespread acceptance of CRTs as an important new learning vehicle.

Equipment necessary to implement Effective Practice: 

Learning Management System like Sakai.

Estimate the probable costs associated with this practice: 

Nominal

References, supporting documents: 

1. Abell, M. Individualizing learning using intelligent technology and universally designed curriculum. The Journal of Technology, Learning, and Assessment, 5(3), 1 (2006)
2. Alexakos, C. et al. Integrating e-learning environments with computational intelligence assessment agents. World Academy of Science, Engineering and Technology, 19,117 (2006)
3. Bersin, J.; Mallon, D. The Future of the LMS. Chief Learning Officer, 10(2), 12 (2011)
4. Billsberry, J., Rollag, K.: New Technological Advances Applied to Management Education. Journal of Management Education. 34(2), 329 (2010)
5. Delone, W., Mclean, E.: The Delone and Mclean Model of Information Systems Success: A Ten-Year Update. Journal of Management information Systems. 19(4), 9 (2003)
6. Diziol, D.; Walker, E.; Rummel, N.; Koedinger, K. Using Intelligent Tutor Technology to Implement Adaptive Support for Student Collaboration. Educational Psychology Review, 22(1), 89 (2010)
7. Graesser, A. Auto Tutor: An intelligent tutoring system with mixed-initiative dialogue. IEEE Transactions on Education, 48(4), 612 (2005)
8. Graves, W.: The Instructional Management System Cooperative: Converting Random Acts of Progress into Global Progress. Educom Review 34(6), 32 (1999)
9. Hunyadi, D.; Pah, I. Ontology used in an e-learning multi-agent architecture. WSEAS Transactions on Information Science & Applications, 5(8), 1302 (2008)
10. Hughes, G.: Using Hybrid Learning to Increase Learner Support and Improve Retention. Teaching in Higher Education. 12(3), 15 (2007)
11. Israel, J.; Aiken, R. Supporting collaborative learning with an intelligent web-based system. International Journal of Artificial Intelligence and Education. 77(1), 3(2007)
12. Jensen, L. Extend Instruction Outside the Classroom: Take Advantage of Your Learning Management System. Computers in Libraries, 30(6), 76 (2010)
13. Kleiman, L., Kass, D.: Giving MBA Programs the Third Degree. Journal of Management Education, 31(1), 81 (2007)
14. Konstantinidis, A.; Papadopoulos, P.; Tsiatsos, T.; Demetriadis, S. Selecting and Evaluating a Learning Management System: A Moodle Evaluation Based on Instructors and Students. International Journal of Distance Education Technologies, 9(3), 13 (2011)
15. Kracznski, D.; Kelly, Melissa. Curriculum Development for Teaching Qualitative Data Analysis Online. Proceedings of QualIT2004: International Conference on Qualitative Research in IT & IT in Qualitative Research (2004)
16. Leelawong, K., ; Biswas, G. (2008). Designing learning by teaching agents: The Betty's Brain System. International Journal of Artificial Intelligence in Education, 18(3), 181(2008).
17. Lin, F.: Designing Distributed Learning Environments with Intelligent Software Agents. Information Science Publishing, Hershey, Pennsylvania (2005)
18. McDuffie, R.; Smith, S.; Murphy, L. Impact of an audit reporting expert system on learning performance: a teaching note. Accounting Education, 15(1), 189 (2006)
19. Najjar, M. On scaffolding adaptive teaching prompts within virtual labs. Journal of Distance Education Technologies, 6(2), 35 (2008)
20. Normand, C., Littlejohn, A., Falconer, I.: A Model for Effective Implementation of Flexible Program Delivery. Innovations in Teaching and Education International. 45(1), 25 (2008)

21. Post, G.; Whisenand, T. An expert systems helps students learn database design. Decision Sciences Journal of Innovative Education, 3(2), 273 (2005)
22. Ping, Z.; Bhattacharyya, S. (2008). Students' Views of a Learning Management System: A Longitudinal Qualitative Study. Communications of AIS, 23, 351 (2008)
23. Rhee, B. et al.: Technology Readiness, Learning Goals, and eLearning. Searching for Synergy, Decision Sciences Journal of Innovative Education, 5(1), 127 (2007)
24. Rogers, E. Diffusion of innovations (5th ed.). New York: Free Press (2003)
25. Roscoe, R.; Chi, M. Understanding tutor learning: Knowledge-building and knowledge-telling in peer tutors' explanations and questions. Review of Educational Research. 77(4), 534 (2007)
26. Sahin, I.; Thompson, A. Using Rogers’ theory to interpret instructional computer use by COE faculty. Journal of Research on Technology in Education, 39(1), 104 (2006)
27. Shroff, R., Vogel, D., Coombes, J. Student E-Learning Intrinsic Motivation: A Qualitative Study. Communications of the Association for Information Systems. 19, 241 (2007)
28. Tang, M., Byme, R.: Regular Versus Online Versus Blended: A Qualitative Description of the Advantages of the Electronic Modes and a Quantitative Evaluation. International Journal on ELearning. 6(2), 257 (2007)
29. Traxler, J. : Current State of Mobile Learning, International Review on Research in Open and Distance Learning, 8(2), 52 (2007)
30. VanLehn, K. The behavior of tutoring systems. International Journal of Artificial Intelligence in Education, 16(3), 227 (2006)
31. Veletsianos, G.; Yersimou, T.; Doering, A. The role of intelligent agents on learner performance. Learning Organizations, 14(4), 300 (2007)
32. Xiaoqing, L, Intelligent Agent Supported Online Education. Decision Sciences Journal of Innovation Education. 5(2), 331 (2007)
33. Yoon, S.; Ardich, A. Situated learning and activity theory-based approach to designing integrated knowledge and learning management systems. International Journal of Knowledge Management, 6(4), 47 (2010)
34. Yueh, H.; Shihkuan, H. Designing a learning management system to support instruction. Communications of the ACM, 51(4), 59 (2008)

Contact(s) for this Effective Practice
Effective Practice Contact: 
Owen P. Hall, Jr.
Email this contact: 
ohall@pepperdine.edu