The Impact of Open Source

Stanford Engineering Online Course, Machine Learning, http://ml-class.org//

            For this week’s blog topic, I elected to examine Stanford Engineering Online course, Machine Learning presented by Professor Ng, the Director of Stanford Artificial Intelligence Lab.  The instructional designer appears to have done a very good job at pre-planning the page layout for the course.  Its layout was designed to help students understand the orienting context, instructional context, and transfer context (Morrison, G., Ross, S. & Kemp, J., 2004).  Its introduction information was divided into five sections; “About The Instructor, About The Class, What is Machine Learning, Course Description, and What You Will Learn.”  Each section provided clarification of student responsibility, course expectation and provided each student with the elements of the principal, “What’s In It For Me, (WIIFM)”.  The course homepage presented a lot of information that was well balanced between text and YouTube videos, taking into account students’ different learning styles (Simonson, M., Smaldino, S., Albright, M., & Zvacek, S. 2009).  In my opinion this online course creates the perfect distance learning environment that is conducive by providing students with all desired information to minimize student’s stress, keeping them informed, reviewing objectives for instruction, and providing example on how they will be evaluated (Simonson, M., Smaldino, S., Albright, M., & Zvacek, S. 2009).

After viewing the online course, I concluded that the course was developed utilizing the ADDIE process.  In each of the sections the professor provided detailed information:

• As to whom they considered the course student population by stating what level of experience they assumed the student currently posed.
• Course objectives were addressed by outlining course expectation, course break down, and course assignment time line etc.
•  Method of instructions.  The students were provided an example of what they could expect to see during a lecture.  The lecture provided samples of activities that accompanied the lecture as method to re-enforce the learning objective.
• Methods of evaluation.  Within the lecture and from the course syllabus, students are provided check- on- learning questions, project assignments in which they were required to apply the information learned and lessons learned as methods of evaluation.
• Feedback methods.  The course provided a section where students or visitors could take the time to provide feedback of their experience with the course.

The course designer has implemented very effective course activities that maximize active learning for the students.  This was accomplished by chucking the information into smaller section for each lecture.  Within each of these lectures were check-on-learning activities that drew student to participate in the learning activity, as well test their knowledge.  The course also had a number of projects that the students had to complete before the course ended.  These projects allowed students to apply their understanding of the knowledge by putting them into practice.  Each of the activities could be measured by utilizing the principal of the Bloom’s taxonomy of the cognitive domain pyramid.  The course appears to start at the lowest level and continue upward towards evaluation (Simonson, M., Smaldino, S., Albright, M., & Zvacek, S. 2009).

References

Wickham, S. (n.d.) Using the Power of W-I-I-F-M. EZine Articles. Retrieved on

Oct 9, 2011. From http://EzineArticles.com/?expert=Steve_Wickham

Morrison, G., Ross, S., & Kemp, J. (2004). Designing effective instructions (4^th ed.).

New York: John Wiley and Sons.

Simonson, M., Smaldino, S., Albright, M., & Zvacek, S. (2009). Teaching and

 learning at a distance foundation of distance education (4^th ed.). New York: Pearson Education Inc.