Mobile devices are omnipresent in our daily lives. They are utilized for a variety of tasks and used multiple times for short periods throughout the day. MOOC providers optimized their platforms for these devices in order to support ubiquitous learning. While a combination of desktop and mobile learning yields improved course performances, standalone learning on mobile devices does not perform in the same manner. One indicator for this is the mismatch between the average usage pattern of mobile devices and the time to consume one content item in a MOOC. Micro learning builds on bite-sized learning material and focusses on short-term learning sessions. This work examines the potential of micro learning activities in the context of MOOCs. Therefore, a framework for video-based micro learning is presented, which features a personalized curriculum. Videos are suggested to the user in a non-linear order that is determined by content dependencies, users’ preferences and watched videos, as well as explicit and implicit user feedback. A mobile application was implemented to test the approach with restructured MOOC content resulting in 58 connected short videos about engineering education – e.g. web technologies and programming languages. The usage data indicates initial curiosity by the users. To improve retention rates, more user motivation will be required for future studies. A survey gathered additional qualitative feedback. While the content suggestions were seen as a vital feature for such an approach, the results showed good interest and acceptance rates to create a better learning experience for MOOCs on mobile devices.

1. From MOOCs to Micro Learning Activities
Max Bothe, Jan Renz, Tobias Rohloff, Christoph Meinel
Learning Engineering Research Group
Chair of Internet Technologies and Systems
Hasso Plattner Institute, Potsdam, Germany
IEEE EDUCON 2019
April 10, 2019
Dubai, UAE
@max_bothe

2. The HPI MOOC Platform
openHPI – Digital Literacy for Lifelong Learners
Chart 2
Max Bothe, 04/10/19
EDUCON 2019
■ Since 2012
■ 600,000+
enrollments
■ Free courses by
HPI professors,
staff and students
■ About digital
technologies,
transformation
and innovation
https://open.hpi.de/
From MOOCs to
Micro Learning
Activities

3. ■ 84% of the openHPI users own a smartphone [1]
■ Accessible via web and mobile apps
■ Usage of mobile devices is lower than desktop usage
■ Web-only, mobile-only & mixed user groups
■ Bad performance of mobile-only users
□ Short session durations
□ Low item discovery
■ User interface is adapted to fit smaller screens of
mobile devices
□ MOOC content remains unchanged
Motivation
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 3
[1] Rohloff et al., Towards a Better Understanding of Mobile Learning in MOOCs, 2018

4. Differences in Usage Patterns
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 4
average
video content length
on MOOC platforms
[2]
average
video playback
duration
average mobile
application session
duration [3]
(10am to 10pm)
[2] Renz et al., Optimizing the video experience in MOOCs, 2015
[3] Böhmer et al., Falling asleep with Angry Birds, Facebook and Kindle: a large scale study on mobile application usage, 2011

5. LANGUAGE LEARNING
■ Often optimized for mobile devices
■ Short content/tasks presented to the user
■ Adaptive to user‘s progress
Micro Learning Approach
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 5
BRAIN TRAINING

6. What are usage patterns and acceptance rates of a
video-based micro learning platform?
How do content suggestions compare to conventional
MOOC navigation?
Research Questions
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 6
RQ 1
RQ 2

7. ■ Mobile-first
■ Implicit curriculum
□ Next content is presented to the user
□ Based on watched content
□ Based on user’s preferences
■ Reduced content length
□ Compared to MOOC content
Implemented Prototype
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 7

8. ■ Content segments builds upon each other
□ Creates knowledge repository with
dependencies
■ Suggested content considers previously
consumed content
□ Ensure user’s knowledge of the topic
□ Watching videos unlocks new content
■ User’s preferences and feedback
influenced content suggestions
Implicit Curriculum
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 8

9. Implicit Curriculum
Knowledge Repository Model
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 9
Video
Group
requires_group
contains
User
watched
requires_video
Category
has_preference belongs_to
was_suggested_to

10. ■ 12 min avg. content length on MOOC platforms [2]
□ From 2 min to 30 min
■ 4-6 min recommended for mobile learning [4]
■ Partitioning long content into smaller chunks
□ Create cohere content chunks
□ 2 slides result in approx. 4 min chunks
■ Changing the slide can also provide topical separation
□ Keep in mind during content production
■ MOOC content implies dependencies
Reduced Content Length
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 10
[2] Renz et al., Optimizing the video experience in MOOCs, 2015
[4] Geng Sun, et al. Micro Learning Adaptation in MOOC: A Software as a Service and a Personalized Learner Model, 2015

11. Implemented Prototype
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 11
■ 58 videos from openHPI courses
and OER videos
□ Beginner/introduction videos
□ Manually structured to work with
implicit curriculum
■ Promotion to openHPI users
□ Social Media channels of
openHPI
□ Global announcement to
openHPI community

12. Learner Behavior
Acceptance Rate
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 12
5277
content
suggestions
673
video
playbacks
2303
discarded
suggestions
535
users
181
active users
Watch
34%
Dismiss only
33%
No activity
33%

13. Learner Behavior
Usage Period
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 13

14. Learner Behavior
Active Days of Usage
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 14

15. Learner Behavior
Watched Videos on Day of Usage
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 15

16. ■ In-app survey for qualitative feedback (N=28)
■ Prompted to the user after three watched videos
□ Later on accessible via submenu
■ The majority used the prototype at home
□ 89% at home
□ 19% in public transport
□ 15% during a break / while waiting
□ 11% at work
Feedback Survey
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 16

17. ■ The reduced content length was perceived as suitable
□ 41% just right, 48% a little bit too short
□ Slightly increase length of content segments
■ Quality of content suggestions can be improved
□ Perceived as neither bad nor very good
■ 78% of the users would like to validate their knowledge (e.g. quiz)
■ Users like for mobile learning:
□ Implicit curriculum (74%)
□ Simple navigation (69%)
■ Users also liked the simple design and asked for more topics
Feedback Survey (cont.)
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 17

18. ■ Automate knowledge repository generation
□ Content-aware partitioning for long content [5]
□ Construction of dependency graph
□ Determination of categories
■ Improve Content Suggestion
□ Optimized suggestion algorithm
□ Consideration of other users’ actions
■ Integration with MOOC platforms
□ Suggest courses
□ Provide different media types
Future Work
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 18
[5] Zhang et al., Automated Segmentation of MOOC Lectures towards Customized Learning, 2016

19. ■ What are usage patterns and acceptance rates of a video-based micro
learning platform? (RQ1)
□ Users showed high interest in such a micro learning concept
□ Usage declined after initial days
■ How do content suggestions compare to conventional MOOC navigation? (RQ2)
□ Increased content discovery
□ More personalized learning paths through individual watch orders
■ How can a micro learning approach support MOOCs?
□ Promotion of MOOCs through content suggestions
□ Reuse content if produced correctly
Conclusion
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 19

20. From MOOCs to Micro Learning Activities
Learning Engineering Research Group
Chair of Internet Technologies and Systems
Hasso Plattner Institute, Potsdam, Germany@max_bothe
max.bothe@hpi.de
Max Bothe, M.Sc.

21. Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 21

22. ■ Slide 5
□ https://www.imore.com/sites/imore.com/files/styles/larger/public/field/image/2014/07/duolingo
_placement_test_screens.jpg?itok=PJ4Ll-6A
□ https://s2.mzstatic.com/r30/Purple69/v4/28/f1/fe/28f1fe8e-066a-34aa-1047-
4a3d884c10d3/screen1136x1136.jpeg
□ https://s5.mzstatic.com/r30/Purple69/v4/79/d2/e1/79d2e15f-82fb-1b5c-f184-
4a4e24233c03/screen1136x1136.jpeg
□ http://a3.mzstatic.com/us/r30/Purple49/v4/ff/89/1c/ff891ccd-4db0-d920-24b4-
90367c5bbfd2/screen2208x2208.jpeg
■ Slide 7
□ https://web.njit.edu/~ad484/images/iphone_frame_for_desktop_view/u0.png
Image Sources
Max Bothe, 04/10/19
EDUCON 2019
From MOOCs to
Micro Learning
Activities
Chart 22