Developing metacognitive skills through the use of blogs in an upper-level undergraduate anatomy course

Presenter First Name: 
Presenter Last Name: 
O'Loughlin, PhD
Year of Presentation: 


Valerie Dean O’Loughlin, Ph.D., Indiana University, Bloomington
Lauren Miller Griffith, Ph.D., Northern Arizona University

What is “metacognition?”

  • “Metacognition is “the ability to monitor one’s current level of understanding and decide when it is not adequate.”*
  • Essentially, a person learns how to learn and becomes more perceptive of one’s learning

* Bransford, JD,  Brown, AL and Cocking, RR (eds) National Academy press, 2000

How can metacognitive techniques be incorporated in this classroom?

  • Frequent, low-risk assessments
  • Exam feedback/review
  • Formative feedback- muddiest point; classroom learning techniques (CATs) - Angelo and Cross, 1993
  • Reflective writing - journals or blogs

Anatomy A480/580: Human Anatomy for Medical Imaging Evaluation
3 cr lecture/lab:  Spring 2010
Taught by VDO
22 students
Systemic study of human anatomy
Compare/contrast medical imaging techniques  
Be able to determine which technique is most suitable in a given diagnostic situation

  • 4 exams (400 pts total)
  • 1 quiz (25 pts)
  • 3 clinical vignettes (25 pts each, 75 pts total)
  • 1 group case study (200 pts)
  • 10 Blog Entries for each Aunt Minnie Case of the Day (10 pts each, 100 pts total)

Aunt Minnie’s case of the day:

  • 10 separate cases over the course of the semester
  • Student writes a blog about his/her experience with the case

Blogs (e-journals) housed on Oncourse (classroom e-platform)
Blog instructions:

  • Provide a summary of the patient problem
  • Describe your perceptions of the images – did you have an idea of what you were seeing? Did you have a better understanding of the case when all was said and done, or was it still unclear?  
  • Evaluate your skill level at identifying the anatomy and determining the pathology in these images.

Blogs graded on completeness of entry and thoughtfulness

What is ‘grounded theory’?

  • Inductive data analysis - first described by Glaser and Strauss (1967)
  • Grounded theory uses inductive analysis to determine what the data is saying (the theory is ‘grounded’ in the data)
  • Researchers immerse themselves in the writing,  determine themes, develop and test the codebook- other literature reviewed only after grounded theory analysis complete

Grounded theory (inductive) analysis of blog entries
IRB approval for study granted - study # 1003001169
Blogs de-identified by 3rd party
Authors read blogs multiple times, determined ‘themes’ and subthemes that appeared multiple times in the blogs
Codebook developed from these themes

  • Both authors tested codebook and codebook revised until themes were mutually exclusive
  • Cohen’s kappa (for interrater reliability) calculated at .69 – considered ‘substantial agreement’ by Landis and Koch (1977) - levels near .7 or greater are considered strong values for interrater reliability

How were blogs coded and analyzed?

  • Blogs subdivided by random ID for student and number of blog
  • Blogs coded by LG - reviewed by VDO
  • VDO calculated frequencies for each code for early semester vs. late semester blogs - determined general trends in data; approximately 1200 codes each for early semester and late semester

As the semester progressed, blogs became more informal and humorous

  • Students felt more at ease in the class and with the instructor
  • Students would use humor when they encountered difficulties instead of let frustration take over

In Summary

  • The use of blogs in A480/580 facilitated student reflection and development of metacognitive skills
  • Instructor was able to visualize progression from ‘novice’ learner to more experienced learner
  • Researchers used grounded theory analysis to methodically assess student development

Future Directions
Evaluation of entire blogs as:

  • Nonreflective
  • Reflective
  • Critically reflective
  • Compare results to those of other researchers

Collect additional data from future class offerings, increase sample size

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