Automated Course Advising System

Students face issues and challenges in making decisions for course registration. Traditionally, students rely on suggestions from academic advisers prior to course registration. Therefore, students spend a considerable amount of time waiting for advisers to help them register for the right subjects. However, the number of students rises yearly, thereby increasing the responsibilities of lecturers. Moreover, academic advisers experience constraints in analysing data during consultations for course registration. Therefore, this study proposes a course recommender model based on collaborative filtering. Collaborative filtering is adopted because it provides recommendations based on students' performance in previous subjects. A dataset from the Information & Communication Technology Centre (ICT) of the University Malaysia Pahang is used to evaluate the proposed model. The evaluation is conducted based on two experiments. The first experiment is performed by calculating the difference between actual and predicted scores to verify prediction accuracy. Results show that the average of the mean absolute error of the proposed model is 0.319, which is highly accurate. The second experiment is conducted by comparing the recommendations of the proposed model with those of experts to validate the course recommendation accuracy of the proposed model. Results of the second experiment show that the proposed model has a 91.06% accuracy rate with an error rate of 8.94%. In addition, average precision is 0.68 and recall is 0.724, which are considered accurate. Therefore, the proposed model can play a vital role in assisting students and academic advisers to recommend the right courses during registration, thereby overcoming the limitations of academic advising.

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“…Given that academic advisers lack time sufficient knowledge about students, effective advising is rarely achieved. [2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

“…Thus, academic advising has become an added responsibility for academic staff. Academic advisers face limitations in analyzing relevant data for student course registration, and academic advising requires psychological as well as people management skills [3,4,6].…”

Section: Introductionmentioning

confidence: 99%

A Proposed Course Recommender Model based on Collaborative Filtering for Course Registration

Salehudin¹,

Kahtan²,

Abdulgabber³

et al. 2019

IJACSA

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“…However, the system suffers with a reported higher error rate because of an inappropriate priority field [7].…”

Section: Background Literaturementioning

confidence: 99%

A Priority Based Course Planning System for Electrical Engineering Department

Laghari¹

2018

IJIET

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Abstract-To create successful students an effective academic advising and course planning program is necessitated. An academic advisor is a link between the student and the institution therefore good advising is critical to the long-term success of an institution. Course planning and advising are trivial processes to ensure students fulfill the degree requirements of an institution in an all-inclusive and structured way, and without encountering unnecessary delays. As experienced academic advisors are hard to find, therefore computer programs doing course planning and academic advising are becoming popular. The United Arab Emirates University is one such institution where students have faced problems due to lack of an appropriate advising system and experienced academic advisors. In this respect, a Priority Based Course Planning System (PBCPS) is devised. PBCPS software package is developed by using the JAVA programming language. The system helps and guide students in selecting appropriate courses for a specific semester. The outcome of the course selection of a subsequent semester is stored in a file to help in course registration.

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“…It is also understood that some students' busy schedules may require schools to conduct advising at a distance. Therefore, universities have experimented with tools such as websites and degree-path advising software to provide guidance for remote students (Laghari, 2014;Polson, 2000). Such tools, including various means of implementing degree mapping, are said to improve retention of adult learners.…”

Section: Literature Reviewmentioning

confidence: 99%

Planning for Veterans' Success! The Degree Map as an Advising Solution

Richardson¹

2014

OLJ

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Due to the expected influx of veterans attending college, it is critical that higher education not only be cognizant of the projected growth but also take a proactive stand and properly plan for these students' success. Academic planning begins with advising professionals developing open communications and becoming equipped to guide veteran students through the matriculation process. Veteran students often have difficulty interpreting university scheduling and frequently have access to only a limited advising staff for course selection information, which may prompt some to not persist in an online degree program. This study's findings suggest the degree map is a powerful tool to help students through class selection and sequencing. The degree map data provides transparency that will contribute to institutional and governmental monitoring for ongoing outreach to student veterans.

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Automated Course Advising System

Cited by 23 publications

References 10 publications

A Proposed Course Recommender Model based on Collaborative Filtering for Course Registration

A Proposed Course Recommender Model based on Collaborative Filtering for Course Registration

A Priority Based Course Planning System for Electrical Engineering Department

Planning for Veterans' Success! The Degree Map as an Advising Solution

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