Learning Management: Graduation

I received my M.Ed in Human Resources Education with a concentration in eLearning from UIUC. I want to thank everyone who has helped me reach this goal, including managers, co-workers, professors, fellow students, family, and friends.

The Master's program coursework included Project Management, Learning Systems Design, Instructional Design, Adult Learning Theory, Program Evaluation and Research, Web 2.0, Computer Ethics, Innovations in eLearning. I was also a member and volunteer of the Chicagoland Chapter of the American Society for Training and Development (CCASTD).

Since graduation, I was certified as an eLearning Instructor with the Princeton Review, and I accepted a full-time position with CEB (formerly Valtera). At CEB, I will be managing small to mid-size employee engagement survey projects, including all project management tasks, data analysis, and reporting. I am very excited about this opportunity, and I hope to periodically share my new found knowledge and experiences with everyone here.

Learning Evaluation: Learning Analytics

Learning analytics is the use of intelligent data, learner-produced data, and analysis models to discover information and social connections, and to predict and advise on learning. (Siemens, 2010) An analytics system includes the information repository itself, as well as a means for data optimization, predictive modeling, forecasting, and statistical analysis.

According to Ferguson (2012), there are 3 factors driving the development of learning analytics in higher education. They are:
1) Big Data
2) Online Learning
3) Political Concerns

When implemeting learning analytics, the following should be considered:
- Methods for visualizing data that are easy to use and understand
- Personalized dashboards
- Standards for the structure of data
- Ethics, privacy, and ownership of data

Data warehouses and the cloud make it possible to collect, manage, and maintain massive amounts of information, and technology platforms can now help us turn a mass of numbers into meaningful patterns. "Data mining uses descriptive and inferential statistics (e.g., moving averages, correlations, and regressions) and complex functions (e.g., graph analysis, market basket analysis, and tokenization) to look inside those patterns for actionable information. Predictive techniques (e.g., neural networks and decision trees) help anticipate behavior and events."(Wagner & Ice, 2012)

Learning Analytics is here to stay. Information gleaned from transactions and interactions in our online lives that can then be summarized in reports in order to provide us with intelligence for making decisions in a shift toward more desirable behavior is extremely valuable!

Resources:
Ferguson, R. (2012). The State Of Learning Analytics in 2012: A Review and Future Challenges. Technical Report KMI-12-01, Knowledge Media Institute, The Open University, UK. http://kmi.open.ac.uk/publications/techreport/kmi-12-01

Siemens, G. (2010). What are learning analytics?. Retrieved from: http://www.elearnspace.org/blog/2010/08/25/what-are-learning-analytics/

Wagner, E., & Ice, P. (2012). Data changes everything: delivering on the promise of learning analytics in higher education. EDUCAUSE Review, July/August. Retrieved from http://www.educause.edu/ero/article/data-changes-everything-delivering-promise-learning-analytics-higher-education.

Learning Tools: Twitter

The new network economy is about communities, collaboration, peer production, and user-generated content. As companies evolve within this new network economy, demands are being placed on internal learning and development departments to assist employees with mitigating the impact of increasing job demands, global workforce redistribution, cross functional projects, and formal information overload. (Pontefract, 2011) Given that many companies are also still burdened financially by recent economic crises in the U.S., learning and development departments are also under pressure to implement extremely cost-effective training solutions.

Due to these economic constraints, many companies are now turning to Web 2.0 tools, such as Twitter, as a means of cultivating formal, social, and informal learning in the workplace. The Twitter platform can be utilized at no cost to the account holder, is accessible anytime, and is especially good for mobile, on-the-go people who can learn anywhere. (Galagan, 2009)

When micro-blogging is encouraged within a company, it can help not only to address on-going employee professional development and training needs, but it also helps to create a company culture in which there is: (Pontefract, 2011)
• Better understanding of the organization across many teams & projects
• Personalization among employees and senior leaders
• Engagement and the feeling that everyone's opinion matters
• Information provided timely, be it formal or social/ community driven

Trainers should not only encourage the use of Twitter among employees for informal learning, but for formal learning as well. Twitter's interface provides a unique presentation platform for storing and sharing learning content and can be used as a delivery platform for training. The favorites tab is the key to designing a course (…) and critical to organizing the delivery of training. “Favorited” content that can be compiled for courses includes: (Wing, 2011)
• Hyperlinks
• Video Links
• Photo Links
• Geo-tagging Links

An example of using Twitter as a platform for course delivery and also a course on the topic, Building a Training Course in Twitter, can be found at: http://twitter.com/#!/ISD20/favorites

Resources:
Galagan, P. (2009) Twitter as a Learning Tool… really. ASTD T+D Magazine. Retrieved from: http://www.astd.org/LC/2009/0409_galagan.htm

Pontefract, D (2011) Micro-blogging is Good for Leadership, Good for Culture. Brave New Org. Retrieved from: http://www.danpontefract.com/?p=267

Wing, T. (2011) App Fusion: Twaining in Twitter. Learning Solutions Magazine. Retrieved from: http://www.learningsolutionsmag.com/articles/623/app-fusion-twaining-in-twitter

Learning Management: Project Planning

This post explores the elements of the initiation and planning stages of project management. As outlined below, the following information should be included in a project proposal and project plan.

Project Proposal
Purpose - Organizational goal
Scope - Breadth and depth of project
Resources - Content and/or personnel assistance needed
Anticipated Outcomes - Deliverables and benefits provided to organization
Constraints - Internal and External
Personal Commitment - Confidentiality and personal standards of conduct

Project Plan
Overview - Describe project concept and history
Phases - Data collection, data analysis, needs assessment, interim reporting
Action Steps - Decisions, meetings, deliverables, review points
Tasks - Chronological sequence of events to complete action steps
Instruments - Schedules, software, surveys, handouts
Cost Estimates - Estimation of resources necessary to complete project

Project reporting will be outlined in a future post.

Image Credit: http://www.mpmm.com/project-management-methodology.php