A Smart Academic Advisor Model for Undergraduate Students

Business and Economics Journal, 2015

Choosing a right course in formative years is very important decision as his future depends on this one decision. Student by himself is not mature enough to take right decision in his early life. Selecting wrong courses means mismatch between student aptitude, capability and personal interest. Faculty or parents have neither the required knowledge nor experience. Since there is no other reliable source generally available that can guide the student towards the most suitable direction, recommender system has been evolved to provide him guidance in selecting a right course. Recommender system is a computer programme prepared with the help of experts where the details of background of the students and their aptitudes help finding a course for his future study. This paper proposes feasible predictions for student's course selection based on their marks and choice of job interest. Clustering technique is used to find structures and relationship within the data. This paper also reveals the research process of preparation of such a recommender system. Business and Economics Journal B us ines s a n d E cono m ic s Jo urna l

Proceedings of the 2014 Zone 1 Conference of the American Society for Engineering Education, 2014

We detail some lessons learned while designing and testing a decision-theoretic advising support tool for undergraduates at a large state university. Between 2009 and 2011 we conducted two surveys of over 500 students in multiple majors and colleges. These surveys asked students detailed questions about their preferences concerning course selection, advising, and career paths. We present data from this study which may be helpful for faculty and staff who advise undergraduate students. We find that advising support software tools can augment the student-advisor relationship, particularly in terms of course planning, but cannot and should not replace in-person advising.

arXiv (Cornell University), 2013

We detail some lessons learned while designing and testing a decision-theoretic advising support tool for undergraduates at a large state university. Between 2009 and 2011 we conducted two surveys of over 500 students in multiple majors and colleges. These surveys asked students detailed questions about their preferences concerning course selection, advising, and career paths. We present data from this study which may be helpful for faculty and staff who advise undergraduate students. We find that advising support software tools can augment the student-advisor relationship, particularly in terms of course planning, but cannot and should not replace in-person advising.

International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies http://TuEngr.com Towards an Innovative Educational Knowledge Model for Intelligent Academic Advising, 2021

Technology is one of the twenty-first century's most important issues, which affects our daily life and future. Since academic institutes have the power to lead the improvement changes. Sustainability values need to be incorporated in Higher Education Institutions’ mission and practice including academic advising services. Academic Advising (AA) is an essential factor that affects the success of any educational institute and sustainability. It is a key to students' success, retention, and loyalty. Digital transformation of AA will help to achieve sustainability, reduce the advisors' workload, improve the advising quality, and enhance students' satisfaction. Much research proved that the low persistence and completion rates highly improved by better advising. The paper discusses the persistent need to develop an intelligent academic advisor system toward fulfilling the responsibility to the stakeholder and leads to enhanced sustainability of such educational institutes. This paper is a part of a research project, aims to improve the current academic advising systems (AAS) in Saudi universities to an intelligent advising system using artificial intelligence. This research study is introduced to investigate the current situation of AA in Saudi universities along with the availability and efficiency of electronic advising systems. We discussed the factors that affect the advising system improvement. We found that the electronic advising system faces many challenges and gaps to innovate new applications that support students’ journeys.

Journal of Computer and Education Research, 2018

Universities offer technical elective courses to allow students to improve themselves in various parts of their majors. Each semester, the students make a decision regarding these technical electives, and the most common expectations students have in this context include, getting education at a better school, getting a better job, and getting higher grades with a view to securing admission into more advanced degree programs. Electing a course on the basis of the interests and skills of the student will naturally translate into achievement. Advisors, in this context, play a major role. Yet, the substantial workload advisors have already assumed prevent them dedicating enough time for exploring the interests and skills of the students, and hence hinder the development of the required relationship between students and their advisors. This study attempts to estimate the achievement level a student intends to elect, on the basis of graduate data received from the database of students of ...

International Journal of Business Information Systems, 2014

Student advising is a vital activity in higher education institutes, yet it is a time consuming effort in academic life. Through experimental research, this article examines whether multiple sources of knowledge are helping academic advisors providing more effective decision to their students. Drawing on multiple knowledge sources, including the students' historical records, university's regulations, students' preferences, and career trends, the article explains why these knowledge sources are essential and discusses ways of constructing it. The article then presents the results of a study of recent developed prototype at University of Bahrain, compares data from the years 2009 through 2011, and discusses implications of the data. It concludes that the proposed model have made significant progress toward more effective decision making for students, but it also identifies a need for further improvement, which can be accomplished through advanced techniques on data mining and artificial intelligence.

International Journal of Machine Learning and Computing, 2014

2015

— the present paper has for purpose to introduce a computerized approach for academic advising process in Moroccan universities in particular we discuss the case of university AbdelMalek Essaadi. This study proposes a prototype of an advisory expert system dedicated to new and incoming students to assist them select the most suitable majors they can apply to and the most convenient institutions they can attend. The expert system proposed uses an Object-Oriented approach to represent the data in the knowledge-base and a profiling phase to simplify the rule-base.

NACADA Journal, 1992

One domain that is appropriate for expert system usage ic student advising. For instance, students in universities can receive advising and counseling regarding financial aid, selection of majors, and course planning. This paper discusses the development of a prototypical computerized system designed to provide advice to high school studenh or college freshmen who are uncertain about the desirability of attending a university or undectded about a potential major. The ondemand consultation gathers information about a student's grades, interesb, test scores, and aptitudes. It assesses student qualifications for admission and evaluates the student's qualifications for a variety of majors. It then recommends curricula the student should consider and recommends appropriate courses for the student's first year.

Proceedings of the Fourth International Conference on Learning Analytics And Knowledge, 2014

Every college student registers for courses from a catalog of numerous offerings each term. Selecting the courses in which to enroll, and in what combinations, can dramatically impact each student's chances for academic success. Taking inspiration from the STEM Academy, we wanted to identify the characteristics of engineering students who graduate with 3.0 or above grade point average. The overall goal of the Customized Course Advising project is to determine the optimal term-by-term course selections for all engineering students based on their incoming characteristics and previous course history and performance, paying particular attention to concurrent enrollment. We found that ACT Math, SAT Math, and Advanced Placement exam can be effective measures to measure the students' academic preparation level. Also, we found that some concurrent courseenrollment patterns are highly predictive of first-term and overall academic success.