Interactive decision support for academic advising
| Date | 04 July 2016 |
| DOI | https://doi.org/10.1108/QAE-03-2013-0011 |
| Published date | 04 July 2016 |
| Pages | 349-368 |
| Author | Abdallah Mohamed |
| Subject Matter | Education,Curriculum, instruction & assessment,Educational evaluation/assessment |
Interactive decision support for
academic advising
Abdallah Mohamed
Faculty of Electrical Engineering, Benha University, Benha, Egypt
Abstract
Purpose – This paper aims to support academic advising, which plays a crucial role in student success
and retention. The paper focuses on one of the most challenging tasks involved in academic advising:
individual course scheduling. This task includes not only careful planning for different courses over
several semesters according to students’ preferences and goals but also must conform to many student
constraints and administrative regulations, some of which may rely on student-specic cases..
Design/methodology/approach – This paper introduces a novel approach that tries to provide
meaningful support to decision makers involved in the course scheduling problem. The approach uses
optimization algorithms to perform a pro-active analysis of the impact of different problem aspects and
eventually suggests a balanced study plan that tries to satisfy both student preferences and advisor
recommendations without violating any constraints.
Findings – An initial application of the proposed system is used to discuss its benets.
Originality/value – The paper introduces a novel approach that uses optimization techniques to
support making efcient decisions during the academic advising process.
Keywords Decision support, Academic advising, Course scheduling
Paper type Research paper
1. Introduction
Academic advising is a critical activity that enhances students’ educational pathways
and academic experiences (Light, 2004). It plays an essential role in linking students to
learning opportunities, helping them realize key learning outcomes and improving their
engagement (Campbell and Nutt, 2008). Providing quality advising is vital to student
success and retention (Fike and Fike, 2008;Habley, 2004;Nutt, 2003;Wiseman and
Messitt, 2010). A survey of 611 student participants with the aim of exploring their
academic advising expectations and experiences signicantly related academic
advising to student success (Young-Jones et al., 2013). Another survey of 944
colleges and universities identied poor academic advising as the number one
characteristic associated with student attrition on their campuses (Beal and Noel, 1980;
Cuseo, 2003). Our need for quality advising becomes more evident during freshman year
and for students with bad academic record (Oliver et al., 2010). Even students who excel
in individual courses may be at risk of dropping out if, among other factors, they receive
poor support to develop and pursue academic goals (Lotkowski et al., 2004;Young-Jones
et al., 2013). Academic advising refers to:
[…] situations in which an institutional representative gives insight or direction to a college
student about an academic, social, or personal matter. The nature of this direction might be to
inform, suggest, counsel, discipline, coach, mentor, or even t each (Gordon et al., 2008).
The current issue and full text archive of this journal is available on Emerald Insight at:
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Interactive
decision
support
349
Received 2 March 2013
Revised 1 March 2014
18 September 2015
Accepted 20 January 2016
QualityAssurance in Education
Vol.24 No. 3, 2016
pp.349-368
©Emerald Group Publishing Limited
0968-4883
DOI 10.1108/QAE-03-2013-0011
One of the most challenging and time-consuming activities of student advising is course
scheduling (Pokrajac and Rasamny, 2006). Guided by academic advisors, this activity
includes careful planning for different courses over several semesters according to
students’ preferences and goals. The prepared course plans must satisfy several student
and university constraints, some of which depend on individual student cases, for
example, the maximum credits to register is correlated with a student’s academic record.
This problem gets more complex when considering a large number of courses that have
different weights, values and time requirements. Student diversity is another aspect that
complicates the problem. The inuence of factors such as ability, effort and task
difculty on students’ success, and hence on course planning, is culturally determined
(Demetriou, 2011). With such complexity, it becomes difcult to make appropriate
decisions when building student-customized course plans, especially for non-expert
advisors.
This problem has been recognized by the research community long time ago (Beal
and Noel, 1980;). Several efforts have been made to provide support for the academic
advisors. Unfortunately, little focus was given to long-term course scheduling (Section
4.1). This is probably due to the fact that universities usually suggest standard study
plans, which rst-year students are encouraged to use. Nevertheless, these plans become
less useful when students have preferences that none of the plans can satisfy. In
addition, students who perform poorly and become on academic probation need custom
plans, which they usually acquire by consulting an academic advisor who revises
students’ current study plans and provides advice on how students can return to good
academic standing. In such cases, it is the responsibility of academic advisors to
carefully analyze each individual case, taking into consideration all inuential factors,
while having the students at the center of the analysis process. It is crucial that students
are then given a sense of control over their current situation and a sense of responsibility
of their academic performance (Demetriou, 2011).
Decision support is a proven means to assist humans to make decisions in case of
semi-structured or unstructured problems encountering incomplete or uncertain
information. The paradigm of decision support suggests pro-active evaluation of
decision alternatives and aims at providing the best knowledge available to decision
makers to make more informed, transparent and effective decisions.
This paper introduces an approach called interactive decision support for course
scheduling (IDiSCS). IDiSCS tries to address the course scheduling problem by
providing meaningful support to decision makers, that is, advisors and advisees. The
scheduling process is performed based on a pro-active analysis of the impact of different
problem aspects. IDiSCS follows an iterative and evolutionary decision support
framework called EVOLVE* (Ruhe and Ngo-The, 2004), which incorporates both
human and computer intelligence to suggest course plans which are reviewed by
decision makers who can either accept one of them or adjust the problem settings and
generate rened plans.
It is important to emphasize that neither the proposed work nor similar technologies
aim to replace one-on-one student–advisor interactions (Feghali et al., 2011;Gordon
et al., 2008;Yarbrough, 2002); an advisor should guide students while allowing them to
take control and responsibility of their academic plans (Erlich and Russ-Eft, 2011).
However, such technologies could be useful for automating some advising functions,
saving time to pay more attention to other tasks such as career counseling.
QAE
24,3
350
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