CIPD has done something amazing. In their latest update to the centres who deliver their qualifications, this includes HRC Online, they have clarified that the use of Artificial Intelligence (AI) is against the rules, and that they are actively looking for AI in assessments by using checkers that look for artificially created assessments.
The reason we at HRC are so happy about this is, we already have those checkers in place, and advise and guide our learners to never use AI when writing assessments or researching. The reasons are multiple:
- Learners aren’t learning if AI is doing the hard work for them. People learn when they are guided by humans, and then write answers themselves.
- We know CIPD is very aware of the situation regarding AI and the negative impact it can have on learning, assessments and the HR industry, so we don’t allow learner-side AI help.
- We are people-centred. We have study mentors, videos, podcasts, and provide assessment based learning. All of this is people talking to people, not robots or AI.
Why we prefer real learning over learners using AI.
AI is one of those things that seems to be shoved into everything at the moment, from fridges to education. Sometimes it can have amazing and transformative effects, for example when diagnosing illnesses. But from a learning perspective, AI is a genuine issue when learners, who may not have time to study properly, take shortcuts using Chat GPT or other generative AI.
HRC doesn’t believe AI helps learners, but we understand the issues that AI solves – lack of time and a feeling of being overwhelmed – that’s why we developed our Level 3 and Level 5 CIPD courses that are easy to use and easy to understand.
We focus on the following, which allows learners to study quickly, but also take no shortcuts, or use AI, to cheat
- We break the learning, and the syllabus, into bite-size chunks. It’s also assessment based, meaning you learn what you need to answer the questions your asked, learning all the important bits.
- We provide videos, articles and even real humans (our study mentors) to allow you to study, and use the limited time you have available to get the most out of learning.
Yes, HRC takes AI assistance and cheating very seriously and has all the checks in place that CIPD rightfully state helps learners actually learn, but we go a step further. We have developed courses that are assessment based, with great support from real people, meaning you don’t need to use AI in the first place.
We think that’s a better way to learn.
Further Technical Reading on AI in e-learning
- “On Perception of Prevalence of Cheating and Usage of Generative AI”
Available at arXiv(
ar5iv - “Chatting and Cheating: Ensuring Academic Integrity in the Era of ChatGPT”
Read the full article on ERIC
ERIC - “Turnitin’s Solution to AI Cheating Raises Faculty Concerns”
Available at Inside Higher Ed(
Inside Higher Ed - “ChatGPT, Cheating, and the Future of Education”
Available on Science News - Moubayed, A., Injadat, M., Nassif, A. B., Lutfiyya, H., & Shami, A.
“E-Learning: Challenges and Research Opportunities Using Machine Learning & Data Analytics,” IEEE Access, vol. 6, pp. 39117-39138, 2018.
Available at: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8417405&isnumber=8274985
DOI: 10.1109/ACCESS.2018.2851790 - Mangaroska, K., Vesin, B., Kostakos, V., Brusilovsky, P., & Giannakos, M. N.
“Architecting Analytics Across Multiple E-Learning Systems to Enhance Learning Design,” IEEE Transactions on Learning Technologies, vol. 14, no. 2, pp. 173-188, 2021.
Available at: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9399793&isnumber=9448368
DOI: 10.1109/TLT.2021.3072159 - Ingavélez-Guerra, P., Robles-Bykbaev, V. E., Pérez-Muñoz, A., Hilera-González, J., & Otón-Tortosa, S.
“Automatic Adaptation of Open Educational Resources: An Approach From a Multilevel Methodology Based on Students’ Preferences, Educational Special Needs, Artificial Intelligence and Accessibility Metadata,” IEEE Access, vol. 10, pp. 9703-9716, 2022.
Available at: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9669174&isnumber=9668973
DOI: 10.1109/ACCESS.2021.3139537 - Thomas, B. & Chandra, J.
“The Effect of Bloom’s Taxonomy on Random Forest Classifier for Cognitive Level Identification of E-content,” 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE), Vellore, India, 2020.
Available at: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9077773&isnumber=9077582
DOI: 10.1109/ic-ETITE47903.2020.2188
