ChatGPT in higher education: Considerations for academic integrity and student learning

1. Abstract:

1.1. 1. Sentiment analysis in articles about lA in higher education. 2. Balance between positive and negative language in the articles analyzed.

1.1.1. Results:

1.1.1.1. 1. Balance between positive and negative language in the articles analyzed. 2. Common topics such as concerns about academic integrity and the use of ChatGPT.

1.1.2. Academic Integrity:

1.1.2.1. 1. Concerns about integrity academic and the use of ChatGPT in student fraud. 2. Discussion about the detection of texts generated by lA in academic tasks.

1.1.3. Avoidance:

1.1.3.1. 1. Discussion about ways to discourage students from using ChatGPT. 2. Examples of students trapped using ChatGPT and its consequences.

2. :

2.1. 1. Importance of examining the representation of stakeholders in the media about AI. 2. Division of the corpus and coding by sections for analysis.

2.1.1. Research Focus:

2.1.1.1. 1. Analysis of the content of articles about the use of ChatGPT in universities. 2. Focus on the representation of stakeholders in the discussion about AI.

2.1.2. Method:

2.1.2.1. 1. Division of the corpus, coding and analysis of sentiment using Nvivo. 2. Use of tools such as Nvivo to guarantee the validity and accuracy of the analysis.

2.1.3. Limitation and Recommendation:

2.1.3.1. 1. Current limitations in the detection of texts generated by lA and recommendations to address them. 2. Need to establish clear guidelines for the ethical use of ChatGPT in academic environments.

2.1.4. Policy:

2.1.4.1. 1. Diversity in university policies on the use of ChatGPT. 2. Need to establish clear guidelines for the ethical use of ChatGPT in universities.

3. Conclusions:

3.1. 1..

3.1.1. Embrace:

3.1.1.1. 1. Debate on the adoption of ChatGPT in higher education. 2. Focus on teaching students to use tools such as ChatGPT in an ethical way.

3.1.2. Discusion:

3.1.2.1. 1. Reflection on the ethical and practical implications of the use of ChatGPT in education. 2. Debate on best practices to adapt academic assignments in the context of the lA.

3.1.3. Voice:

3.1.3.1. 1. Analysis of who speaks in the articles and how stakeholders are represented. 2. Importance of the representation of different voices in the discussion about AI in education.