Presented by
Dr Vanessa Hughes
Sydney Nursing School
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Cohort: First Year Bachelor of
Nursing Advanced Studies
Students
Nursing focus: Clinical notes, family/social history and diagnosis is provided
Content: Focuses on connecting the signs/symptoms observed with the underlying pathophysiology
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The Evolution of Online Case Based Learning in NURS1005
2012 2013 2014 2015
Passive PDF Online module + videos +
PDF worksheet
Smart Sparrow
Adaptive Learning
Smart Sparrow technology has made it possible to:
• embed videos into the lesson
• create lessons that adapt to the students responses
• create an active learning environment
• test student knowledge and understanding
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Purpose of the Online Case Study Lesson
– Replaces 1 hour of face to face teaching
– Covers important content in greater detail
– Connects bioscience theory with clinical practice
– Students receive formative feedback that enables them to: a.
Check their answers b.
Understand the level of detail and knowledge expected c.
Practice answering similar types of questions to the ones included in their Pathophysiology Workbook Assessment
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1. Trigger Video
2. Clinical Notes
3. MCQ or
Short Answer Question
Incorrect Answer Correct Answer
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Guidance Model Answer
Page 5

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Using Learning Analytics to Improve Learning and Teaching
– How long did students spend watching each video? Did they watch all of it?
– Were the questions too hard/easy? What needs to be clarified?
– What are the concepts that all students struggle with? What can I do to facilitate their understanding of the content?
– How long did each exercise take? Are they disengaging at some point?
– I would never have been able to easily answer any of these questions without Smart Sparrow Analytics.
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Week 1 Week 2
96% of students attempted the lesson 85% of students attempted the lesson
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Simple overview of how students engaged with the activity
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Anonymous Participation Students Enrolled in Smart Sparrow
49% completed the activity
94% completed the activity
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Ability to Track Learning Pathways
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Short Answer Responses
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Student Feedback (1= Strongly disagree, 5= Strongly Agree)
The videos in this module helped me to better understand the content.
I feel that completing this module will help me complete my pathophysiology workbook.
I feel that the feedback provided encouraged me or helped me find the answer when I made a mistake.
The model answers provided helped me understand what is expected of me and helped me understand what I needed to know about this topic.
Week 1 (n=179) Week 2 (n=154)
4.11
4.11
4.06
4.27
4.54
4.05
4.28
4.49
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Using Analytics to Track Student Performance
Using the analytics students can be categorised as:
– No risk
– Low risk
– High risk
This data can be used to:
– send personalised emails to students
– identify students for follow up using the Track & Connect program
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Using analytics to provide personalised student feedback
Students are sent a personalised email (weekly) (via SRES) based on their risk category.
 No risk – congratulations on completing all activities
 Low risk – encouragement to improve
 High risk – encouragement to improve, support and advice
Students at risk are emailed with their advisors details as well as the contact details for other university support services.
The email also contains links to additional resources that address common misconceptions found in the short answer responses.
This email feedback system has lead to several student problems being identified by the end of week 3.
It is hoped that this system will lead to a reduction in absent fails and enable students who are falling behind to get the help they need earlier in the semester.
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Important Points
– Numbers only tell half the story: a.
Use a combination of MCQ and short answer questions.
b.
By quickly scanning short answer responses you can identify common misconceptions.
– Start small and build on the lesson.
– Keep it simple, too many trap states and pathways can lead to errors.
– Guidance to correct mistakes can be simple e.g. a recommended reading, video etc.
If you have not used SRES (Student Relationship and Engagement System), you will need to contact Adam Bridgeman ( adam.bridgeman@sydney.edu.au
) to be registered as a user.
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