Track 5. Learning Analytics: The good, the bad and the ugly Authors: Elena García-Barriocanal, Miguel-Angel Sicilia, Salvador Sánchez-Alonso and Juan-José Cuadrado. https://youtu.be/HuLia4mKYFo

1. Agilemethodsasproblem-basedlearning
designs:settingandassessment
E. García-Barriocanal, M.A. Scilia, S. Sánchez-Alonso, J.J. Cuadrado
(University of Alcalá, Spain)
Teem2018,Salamanca(Spain)

2. Whatarewe
aimingto?
 Report a case study to introduce learning analytics in
an instructional design for Advanced Software
Engineering courses using problem-based learning
approach.

3. Whatisthe
general
context?
 Problem-based learning approach.
 Agile methods: SCRUM.
 Jira Software.
 GitHub.

4. Whichtoolshaveweusedforanalysis?

5. Whatarethe
mostrelevant
findings?
 Regarding ongoing work, Jira graphical reports are
useful to:
 Track the ongoing progress both of group and individual.
 Early detect possible fails.
 Detect of bottlenecks.
 Detect poor work in analysis phase.
 Detect poor software quality.
 Regarding assessment:
 Bimodal distribution on student final grade and the group
output.
 Peer assessment moderately correlates with individual
grades.
 Accomplished effort accumulate per group significantly
correlates with average individual grade per group.

6. Wayforward
 Pitfalls:
 Inconsistent data on GitHub and Jira (per student).
 Learn SCRUM and the use of Jira Software introduces bias.
 Actions to be taken:
 Rerun the pilot.
 Pre-course on SCRUM and Jira Software.
 Reconsider some ítems in assessment.