Abstract:

The evaluation of learning by using artificial intelligence (AI) in the teaching process is a critical aspect to measure the effectiveness of interventions and continuously improve the quality of education. Each type of model has its own advantages and limitations, and the choice of model depends on the context in which it is used. Taking into consideration the advantages provided by the use of AI to teach our classes and the teachers who teach the subject of Molecular Bases of Cancer (BMC) in the 7th semester of the Biology degree, we consider it pertinent to introduce this tool in the teaching process. Due to the nature of the scientific information required to fulfill the BMC subject syllabus, it was decided to use the GPT Chat, a generative language model based on transformers. During the design implementation process, the learning evaluation process would be done through the analysis of the sequence of questions asked by the student to the AI during the search for information on a particular topic assigned at the beginning of the semester and the delivery of a written report. Given that using AI to enrich the class can make the evaluation process difficult, the following key aspects were established and defined to carry out a learning evaluation that is as impartial and objective as possible.
1. Planning: carry out detailed planning of the activities that will be carried out in class;
2. Selection of the AI: the result obtained depends on the appropriate selection of the AI language model to be used for the development of the topics;
3. Rehearse: rehearse the chosen AI tools, prior to the start of school activities, in order to know the possible results that can be obtained and assign a value to each of the elements identified as a result;
4. Adjustments: make the necessary adjustments and rehearse;
5. Define what is going to be evaluated: we decided not to evaluate the final product generated by the AI, but rather the reasoning that the student follows to obtain it.

By applying these 5 key aspects we were able to verify that the students achieved significant learning, in addition to becoming familiar with the use of AI.

Acknowledgement:
This work had the financial support of the PAPIME Program of the DGAPA UNAM with the projects PE-211323 and PE-200523.

Keywords:

Teaching-learning evaluation, ChatGPT, IA.