LADA: A learning analytics dashboard for academic advising

Francisco Gutiérrez, Karsten Seipp, Xavier Ochoa, Katherine Chiluiza, Tinne De Laet, Katrien Verbert

Research output: Contribution to journalArticlepeer-review


From the perspective of Learning and Educational Technologies, academic advising has been one of the most overlooked aspects of academic support systems, despite being critical for the learning process and final success of students. The majority of higher education institutions provides simple technical support to academic advisers with basic descriptive statistics. This article presents the general design and implementation of a Learning Analytics Dashboard for Advisers (LADA), to support the decision-making process of academic advisers through comparative and predictive analysis. Moreover, this work evaluates the use of this tool to support decision-making of actual advisers in two different higher education institutions (University A, University B), compared with more traditional procedures and tools. Results indicate that LADA enables expert advisers to evaluate significantly more scenarios (Median = 2), especially for high advising difficulty cases with students that failed many courses (MedianA=3,MedianB=2.5), in a not-significantly different amount of time. For inexperienced advisers, LADA is perceived as a valuable tool for more accurate and efficient decision-making, as they were able to make informed decisions in a similar amount of time compared to the experts. These results are encouraging for further developments in the field.

Original languageEnglish (US)
Article number105826
JournalComputers in Human Behavior
StatePublished - Jun 2020


  • Academic adviser
  • Academic advising
  • Data-driven decision-making
  • Learning analytics
  • Visualization

ASJC Scopus subject areas

  • Arts and Humanities (miscellaneous)
  • Human-Computer Interaction
  • General Psychology


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