CoChat
Sign Up
Cited by 429Artificial Intelligence in EducationIntelligent Tutoring Systems and Adaptive LearningAI in Service Interactions

The DOI matches its Crossref record; 46 of the 47 references it cites were found in a registry or an index.

The impact of a virtual teaching assistant (chatbot) on students’ learning in Ghanaian higher education

Open access
Essel, Harry Barton, Vlachopoulos, Dimitrios, Tachie-Menson, Akosua, Johnson, Esi Eduafua, Baah, Papa Kwame·2022·International Journal of Educational Technology in Higher Education
DOI 10.1186/s41239-022-00362-6
Open this paper in CoChat — free accountOpen PDF

Abstract

Abstract Chatbot usage is evolving rapidly in various fields, including higher education. The present study’s purpose is to discuss the effect of a virtual teaching assistant (chatbot) that automatically responds to a student’s question. A pretest–posttest design was implemented, with the 68 participating undergraduate students being randomly allocated to scenarios representing a 2 × 2 design (experimental and control cohorts). Data was garnered utilizing an academic achievement test and focus groups, which allowed more in depth analysis of the students’ experience with the chatbot. The results of the study demonstrated that the students who interacted with the chatbot performed better academically comparing to those who interacted with the course instructor. Besides, the focus group data garnered from the experimental cohort illustrated that they were confident about the chatbot’s integration into the course. The present study essentially focused on the learning of the experimental cohort and their view regarding interaction with the chatbot. This study contributes the emerging artificial intelligence (AI) chatbot literature to improve student academic performance. To our knowledge, this is the first study in Ghana to integrate a chatbot to engage undergraduate students. This study provides critical information on the use and development of virtual teaching assistants using a zero-coding technique, which is the most suitable approach for organizations with limited financial and human resources.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s41239-022-00362-6

Cites

46 of 46 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 47 references

Research works printed but not linked: 8

  1. Essel, H. B., Butakor, P. K., & Nortey, S. (2019). Summative e-examination for high stake assessment in higher education: A case of undergraduate students at the Kwame Nkrumah University of Science and Technology. Global Journal of Human-Social Science: Arts & Humanities-Psychology, 19, 03.
  2. Gupta, S., Jagannath, K., Aggarwal, N., Sridar, R., Wilde, S., & Chen, Y. (2019). Artificially intelligently (AI) tutors in the classroom: A need assessment study of designing chatbots to support student learning. Twenty-third pacific Asia conference on information systems. 8–12 July, Xi’an, China.
  3. Hasançebi, B., Terzi, Y., & Küçük, Z. (2020). Distractor analysis based on item difficulty index and item discrimination index. Gümüshane University Journal of Science Institute, 10(1), 224–240.
  4. Hiremath, G., Hajare, A., Bhosale, P., Nanaware, R., & Wagh, K. S. (2018). Chatbot for education system. International Journal of Advance Research, Ideas and Innovations in Technology, 4(3), 37–43.
  5. Okonkwo, C. W., & Ade-Ibijola, A. (2020). Python-Bot: A chatbot for teaching python programming. Engineering Letters, 29(1), 25–34.
  6. Satam, S., Nimje, T., Shetty, S., & Kurle, S. (2020). Mentoring Chatbot using Artificial Intelligence Framework. SAMRIDDHI: A Journal of Physical Sciences, Engineering and Technology, 12(1), 151–156.
  7. Smutny, P., & Schreiberova, P. (2020). Chatbots for learning: A review of educational chatbots for the Facebook Messenger. Computers and Education. https://doi.org/10.1016/j.compedu.2020.103862,103862 · DOI
  8. Tsyhaniuk, D., & Akenten, W. N. (2021). Examining budgeting and fund allocation in higher education. Financial Markets, Institutions and Risks. https://doi.org/10.21272/fmir.5(4).128-138.202 · DOI

Cited by

Sorted by citations

Related

See all

Metadata

Authors
Essel, H. B., Vlachopoulos, D., Tachie-Menson, A., Johnson, E. E., & Baah, P. K.
Affiliations
  • Kwame Nkrumah University of Science and Technology (GH)
  • Erasmus University Rotterdam (NL)
Corresponding author
Vlachopoulos, Dimitrios
ORCID
Venue
International Journal of Educational Technology in Higher Education
Publisher
Springer Science and Business Media LLC
Published
2022-11-15
Volume
19
Issue
1
ISSN
2365-9440 (ISSN-L)
DOI
10.1186/s41239-022-00362-6
OpenAlex
W4308947461
Cited by
428
References
47
Citations by year
2026: 100 · 2025: 146 · 2024: 114 · 2023: 67 · 2022: 1
FWCI
81.21
Type
journal article
Language
en
Open access
Licence
Locations
  • International Journal of Educational Technology in Higher Education (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, other-oa)
  • Greater South Information System
Topics
  • Social Sciences › Education › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
Keywords
chatbots, virtual teaching assistants, artificial intelligence in education, academic performance, undergraduate students, student perceptions, Ghanaian higher education

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review