Project 2

LDT630

Project 2 Data Analytics in Action

Educational data plays an important role as we measure the effectiveness of the course design and implementation. In Project 2, we researched major learning management systems (LMSs) to know their features, especially data analytics. The assignments were threefold. We created a scavenger hunts worksheet, evaluated course quality assurance standards, and summarized them in an educational data collection research journal article.

1. LMS Scavenger Hunt

As an instructional/learning designer, to improve the learner experience, conducting regular data analytic cycles in the design team involves educational data mining and using big data automatically collected in LMS.

I reviewed each LMS's features, capabilities, reporting, and data analytics of Blackboard Learn from Anthology, Design2Learning (D2L) from Brightspace, Canvas from Instructure, and open-source Moodle. I also added to research on data security & user privacy approach, accessibility, and multilanguage support.

yamamotor-LMS Scavenger Hunt Worksheet.pdf

2. Quality Assurance Standards Evaluation

Institutions and organizations use rubrics, checklists, or scorecards to evaluate the effectiveness of courses.

Quality Matter is a widely used QA standard in the US, but since I don't work at a higher education institution, I don't have access to the resource. Instead, I used the Quality of Course Teaching and Instructional Practice (QCTIP), one of a series of scorecards from the Online Learning Consortium (OLC) to identify the pros and cons of the scorecard.

yamamotor-evaluation of QA standard.pdf

3. Learning analytics journal article

The 10-page article's audience is instructional designers and researchers in educational research who subscribe to the Journal of Applied Instructional Design.

yamamotor-journal article-final submit.pdf

The Process and Reflection

Process

Review how to write academic papers and journal articles.
Review the journal and audience you are writing for.
Brainstorm the topics and align them with the requirements the assignment provided.
Do a preliminary read once the topics shape a rough logical flow.
Take notes of idea development, new findings from reading sources, and references.
Structure outline of the article on solid and debatable ground.
Develop the outline into paragraphs.
Review the thesis often to develop cohesive narratives. Know writing takes time and schedule to focus on a portion per session. Let it sleep and come back the next day.
Intentionally incorporate exercise or daily chores between writing sessions for the brain to rest in diffused mode.
The brain can progress ideas at any time. Write it down when it surfaces.
When a narrative flows, I usually think about a specific learner group. Think beyond data points and imagine what it means to the individual.
One by one, reach a conclusion.
Clean it up and double-check with Turn It In and Tutor.com.
If someone provided constructive feedback, review the article with insight from the feedback.

In the end

It has been a while since I wrote an academic paper, so I needed to get into the rhythm of writing. Reading articles from peer-reviewed journals was helpful in knowing the expectations and structures for the article.

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References

1EdTech. (n.d.). Learning Tools Interoperability. IMS Global Learning Consortium. https://www.imsglobal.org/activity/learning-tools-interoperability

AAC&U. (n.d.). VALUE Rubrics. AAC&U. https://www.aacu.org/initiatives/value-initiative/value-rubrics

Adams, S, Buchan, T, Garth-McCullough, R & Hampton, M. (2022, September 19). Digital Learning Instructional Strategy Guide Series. Achieving the Dream and Every Learner Everywhere. https://www.everylearnereverywhere.org/resources/

Anthology. (n.d.a). Blackboard Analytics for Learn | LMS Reporting Tools. Blackboard. https://www.blackboard.com/teaching-learning/data-and-analytics/analytics-for-learn

Anthology. (n.d.b). Student Data Management System—Blackboard Intelligence. Blackboard. https://www.blackboard.com/teaching-learning/data-and-analytics/blackboard-intelligence

Blake-Plock, S. (2019). Analytics and Visualization. In Walcutt, J. J., & Schatz, S. (Eds.) Modernizing Learning: Building the Future Learning Ecosystem. Advanced Distributed Learning Initiative. https://adlnet.gov/publications/2019/04/modernizing-learning/

Bouchrika, I. (2022, December 20). 11 Top Trends in Higher Education: 2023 Data, Insights & Predictions. Research.com. https://research.com/education/trends-in-higher-education

Brightspace. (n.d.). About tracking content completion and participation. https://documentation.brightspace.com/EN/le/content/instructor/tracking_completion_participation.htm

Davies, R., Allen, G., Albrecht, C., Bakir, N., & Ball, N. (2021). Using Educational Data Mining to Identify and Analyze Student Learning Strategies in an Online Flipped Classroom. Education Sciences, 11(11), 668. https://doi.org/10.3390/educsci11110668

Dorn, E., Law, J., & Ram, S. (2020, November). Higher education enrollment: Inevitable decline or online opportunity? McKinsey. https://www.mckinsey.com/industries/public-and-social-sector/our-insights/higher-education-enrollment-inevitable-decline-or-online-opportunity

Fritz, J. (2017). Using Analytics to Nudge Student Responsibility for Learning: Using Analytics to Nudge Student Responsibility for Learning. New Directions for Higher Education. 2017(179), 65–75. https://doi.org/10.1002/he.20244

Heinemann, B., Ehlenz, M., Görzen, S., & Schroeder, U. (2022). xAPI Made Easy: A Learning Analytics Infrastructure for Interdisciplinary Projects. International Journal of Online and Biomedical Engineering (IJOE), 18(14), 99–113. https://doi.org/10.3991/ijoe.v18i14.35079

Lumina Foundation (2022, April 20). Stress weighs heavily on those who remain in college, a new Gallup-Lumina study finds. https://www.luminafoundation.org/news-and-views/stress-weighs-heavily-on-those-who-remain-in-college-a-new-gallup-lumina-study-finds/

Moodle. (n.d.). Students at risk of dropping out—MoodleDocs. https://docs.moodle.org/401/en/Students_at_risk_of_dropping_out

Morgan, J. (2022, October 12). Supporting mental health with data and analytics through improved education policy. SAS Voices. https://blogs.sas.com/content/sascom/2022/10/12/supporting-mental-health-with-data-and-analytics-through-improved-education-policy/

Nehiri, N., & Aknin, N. (2021). A Proposed Learner’s Data Model: Integrating Informal Learning and Enhancing Personalization and Interoperability. International Journal of Emerging Technologies in Learning (IJET), 16(08), 173. https://doi.org/10.3991/ijet.v16i08.19833

Opendoors. (n.d.). IIE Open Doors / International Students. IIE Open Doors / International Students. https://opendoorsdata.org/data/international-students/

Senge, P. M. (1994). The fifth discipline: The art and practice of the learning organization. New York: Doubleday.

Teasley, S. D., Love, J., & DeMonner, S. (2021, July 20). Show Students Their Data: Using Dashboards to Support Self-Regulated Learning. Educause. https://er.educause.edu/articles/2021/7/show-students-their-data-using-dashboards-to-support-self-regulated-learning

Wood, J. (2022, January 27). These 3 charts show the global growth in online learning. World Economic Forum. https://www.weforum.org/agenda/2022/01/online-learning-courses-reskill-skills-gap/

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