This document discusses enriching learning analytics data with lesson observation context. It notes that typical learning analytics only capture minimal actor-verb-object data from tools and don't provide context about why students interacted. A project in Estonia developed open educational resources and collected learning analytics and observation data on their use in classrooms. The data showed interaction frequencies but lacked context. Integrating learning design, observation annotations, and multi-modal analytics could provide a more comprehensive view of classroom digital practices.

1. Enriching the Context for
Learning Analytics with Lesson
Observation Data
Mart Laanpere
Senior researcher @ Centre for Educational Technology
Tallinn University, Estonia

2. Counting clicks is not enough
• National strategy of education: towards more creative, collaborative
and self-directed learning with the help of digital technologies
• Typical LA does not consider specifics of classroom research
• H5P and most of other xAPI-compliant Learning Object tools report
only minimum data: Actor, Verb, Object (no Context): we don’t know
WHY they clicked, was it assigned by teacher, was it collaborative
• Research questions:
• What are the limitations of existing LA services enables in the research about
classroom practices involving use of interactive learning resources?
• How can we improve Learning Analytics to effectively make sense of the
digital practises in classroom?

3. DigiÕppeVaramu project
• Public procurement process by Ministry of Education and Research: to
produce OER that covers the whole national curriculum for Estonian
high schools (grades 10 – 12, 6 domains)
• The bid by Tallinn University covered 4 curriculum domains out of 6:
mathematics, science (physics, biology, chemistry, geography), social
studies (history, civics, human studies), arts (music, visual arts)
• Our primary aim was not to replace existing textbooks, but to enhance
• Open license: Creative Commons – Attribution (CC-BY)
• Created H5P learning objects (10 000+) were piloted by 28 teachers in
20 schools over the period of 2 months
• Binders with H5P learning objects were created by pilot teachers using
eSchoolbag as an aggregator

4. The platform
The national catalogue of
digital learning resources
DigiÕppeVaramu
Vara.eKoolkott.ee
eKoolikott.ee
H5P
object
H5P
object
H5P
object
Topic Binder
Chapter
Sub-chapter
Resource
Resource
Chapter
Sub-chapter
Resource
Drupal 7
H5P +
Math support
New templates
LOM-based
Learning Object Repository
Single Sign-On:
ID card, mID, SiS
(unfortunately,
not used in our
study)
LearningLocker
xAPI Learning
Record Store
Metadata
harvesting
OAI-PMH

5. Showcase: e-Koolikott.ee (e-Schoolbag)

6. LRS data: Verb frequencies in statements

7. LRS data for two lessons

8. .netLePlanner.ee: visualising Learning Design

9. Levels of learner’s contribution
Level Learner’s contribution Examples of tools
6: Creating Creates a new resource from
scratch
GeoGebra, iMovie, Aurasma, PhotoStory,
GarageBand, H5P
5: Remixing Rips, mixes, cuts, adds visuals
or subtitles
“Hitler gets angry” video, 9gag, samples,
GeoGebra, GDocs
4: Expanding Curates, adds external
resources to collection
Scoop.it, blog
3: Submitting Solves a task, submits to
teacher for the feedback
Kahoot, Khan Academy, online tests,
worksheets made with Gdocs
2: Interacting Self-test, simple game LearningApps, HotPotatoes, SCORM
1: Annotating Likes, bookmarks, comments Youtube video, ePub, PDF, Web page
0: Consuming Views, listens, reads PowerPoint, PDF, video

10. Lesson observations: Observata protocol (xAPI)

11. Additional data collection
• Teachers reflected after every lesson, using semi-structured template
• Online questionnaires:
• Before pilot: Concern-Based Adoption (CBAM), only teachers
• After pilot: technology acceptance (UTAUT), both teachers and students
• Pilot lessons were video recorded
• Too much (qualitative) data, this approach cannot be automatised

12. Future vision: multi-perspective LA for
classroom research
Multimodal LA
data from LRS
Learning Design
xAPI-annotated
observations

13. Conclusions
• In the context of classroom research, there is a need to enrich the
Learning Analytics data with Learning Design (intentions,
assignments) and Lesson Observation (context)
• Tools like LePlanner and Observata might provide solution, but we
need to figure out how to connect intention and context data to xAPI
statements
• Identification of users is necessary, new and stricter privacy
protection laws are making it more difficult
• It would be interesting to collect the data on stray activities of
students during the lessons, but it would violate their privacy