TY - JOUR
T1 - LADA
T2 - A learning analytics dashboard for academic advising
AU - Gutiérrez, Francisco
AU - Seipp, Karsten
AU - Ochoa, Xavier
AU - Chiluiza, Katherine
AU - De Laet, Tinne
AU - Verbert, Katrien
N1 - Funding Information:
Part of this work has been supported by the Research Foundation Flanders (FWO, grant agreement no. G0C9515N) and the Secretary of Higher Education, Science, Technology and Innovation, Ecuador (SENECYT, Project PIC-15-ESPOL-FWO-001).
Funding Information:
Part of this work has been supported by the Research Foundation Flanders (FWO, grant agreement no. G0C9515N ) and the Secretary of Higher Education, Science, Technology and Innovation , Ecuador (SENECYT, Project PIC-15-ESPOL-FWO-001 ).
Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2020/6
Y1 - 2020/6
N2 - 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.
AB - 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.
KW - Academic adviser
KW - Academic advising
KW - Data-driven decision-making
KW - Learning analytics
KW - Visualization
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U2 - 10.1016/j.chb.2018.12.004
DO - 10.1016/j.chb.2018.12.004
M3 - Article
AN - SCOPUS:85058469687
SN - 0747-5632
VL - 107
JO - Computers in Human Behavior
JF - Computers in Human Behavior
M1 - 105826
ER -