StuA: An Intelligent Student Assistant

Lodhi, Pooja; Mishra, Omji; Jain, Shikha; Bajaj, Vasvi

doi:10.9781/ijimai.2018.02.008

Cited by 17 publications

(15 citation statements)

References 9 publications

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“…The main characteristics of AI, described in all five studies, are the parallels between the human brain and artificial intelligence. The authors conceptualise AI as intelligent computer systems or intelligent agents with human features, such as the ability to memorise knowledge, to perceive and manipulate their environment in a similar way as humans, and to understand human natural language (see Huang, 2018;Lodhi, Mishra, Jain, & Bajaj, 2018;Welham, 2008). Dodigovic (2007) defines AI in her article as follows (p. 100):…”

Section: Understanding Of Ai and Critical Reflection Of Challenges Anmentioning

confidence: 99%

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Systematic review of research on artificial intelligence applications in higher education – where are the educators?

Zawacki‐Richter

Marín

Bond

et al. 2019

Int J Educ Technol High Educ

1,581

468

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According to various international reports, Artificial Intelligence in Education (AIEd) is one of the currently emerging fields in educational technology. Whilst it has been around for about 30 years, it is still unclear for educators how to make pedagogical advantage of it on a broader scale, and how it can actually impact meaningfully on teaching and learning in higher education. This paper seeks to provide an overview of research on AI applications in higher education through a systematic review. Out of 2656 initially identified publications for the period between 2007 and 2018, 146 articles were included for final synthesis, according to explicit inclusion and exclusion criteria. The descriptive results show that most of the disciplines involved in AIEd papers come from Computer Science and STEM, and that quantitative methods were the most frequently used in empirical studies. The synthesis of results presents four areas of AIEd applications in academic support services, and institutional and administrative services: 1. profiling and prediction, 2. assessment and evaluation, 3. adaptive systems and personalisation, and 4. intelligent tutoring systems. The conclusions reflect on the almost lack of critical reflection of challenges and risks of AIEd, the weak connection to theoretical pedagogical perspectives, and the need for further exploration of ethical and educational approaches in the application of AIEd in higher education.

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Section: Understanding Of Ai and Critical Reflection Of Challenges Anmentioning

confidence: 99%

“…The latter presents StuA, an interactive and intelligent student assistant that helps newcomers in a college by answering queries related to faculty members, examinations, extra curriculum activities, library services, etc. (Lodhi et al, 2018).…”

Section: Intelligent Tutoring Systemsmentioning

confidence: 99%

Systematic review of research on artificial intelligence applications in higher education – where are the educators?

Zawacki‐Richter

Marín

Bond

et al. 2019

Int J Educ Technol High Educ

1,581

468

View full text Add to dashboard Cite

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“…It recognizes which courses have been taken and which are expected for the next semester. Author in [22] represents an intelligent single-task system designed to be a virtual assistant for the new-comer student to reply to their questions about the university. It is designed using a rule-based system and implemented using CLIPSJNI and JAVA.…”

Section: Single-tasking Systemmentioning

confidence: 99%

From Traditional to Intelligent Academic Advising: A Systematic Literature Review of e-Academic Advising

Assiri¹,

AL-Ghamdi²,

Brdesee³

2020

IJACSA

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Academic advising plays a crucial role in the achievement of the educational institution purposes. It is an essential element in solving students' academic problems and maximizing their satisfaction and loyalty. Universities around the world have always tried to improve academic advising to personalize the student's experience. In fact, technology has the power to improve the advising process and facilitate its corresponding tasks and this has historically taken different forms. Accordingly, this paper provides an overview of academic advising and the technologies proposed to improve it. The authors present a systematic literature review on research papers that proposed an electronic academic advising system to view the research trends and identify electronic academic advising major challenges. The main contribution of this paper is to survey the different aspects and trends about the electronic systems that have been proposed to serve academic advising. This paper is a part of major research that aims to transfer the traditional academic advising to one based on Artificial Intelligence, via the current phase of academic advising.

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“…With the accelerated expansion of technologies across the K–12 curriculum, students’ opportunities to engage with education-focused artificial intelligence (AI) software have increased (Touretzky et al, 2019). AI is described not as a cognitive process but as a multitude of components that constitute intelligence, such as problem solving, perception, and language identification; researchers have been able to develop AI software that mimics human decision making from its experiences (Lodhi et al, 2018). Society has more access to and interacts with AI devices more regularly and intimately than previous generations (McCarthy, 2007; Touretzky et al, 2019).…”

Section: Artificial Intelligencementioning

confidence: 99%