Learning desk

MultiAgent EDU StackGather good sources. Teach what matters.
T5TauricResearch/TradingAgentsT5A Man Who Invented Modern AI (Before Everyone Else) – Jürgen Schmidhuber [video]T5GPT-4 finished training four years ago todayT5AI Settles a 25 Year-Old Problem We Left BehindT5What it was like working on LLMs and security at Meta (2022-2026)T5Ask HN: How do you go from writing code to deploying with agents?T5What Happened: OpenAI and HuggingFaceT5Apple says Mac users in China can connect to Alibaba's Qwen AI serviceT5Show HN: Try Benzi – A coding harness/agent beating Claude Code itself on SonnetT5The AI Apocalypse Is HereT3Auto mode is now the default in Claude Code for Pro, Max, and Team plansT5Show HN: Tura – Build agent that uses 80% less token and delivers better resultsT5TauricResearch/TradingAgentsT5A Man Who Invented Modern AI (Before Everyone Else) – Jürgen Schmidhuber [video]T5GPT-4 finished training four years ago todayT5AI Settles a 25 Year-Old Problem We Left BehindT5What it was like working on LLMs and security at Meta (2022-2026)T5Ask HN: How do you go from writing code to deploying with agents?T5What Happened: OpenAI and HuggingFaceT5Apple says Mac users in China can connect to Alibaba's Qwen AI serviceT5Show HN: Try Benzi – A coding harness/agent beating Claude Code itself on SonnetT5The AI Apocalypse Is HereT3Auto mode is now the default in Claude Code for Pro, Max, and Team plansT5Show HN: Tura – Build agent that uses 80% less token and delivers better results
← Dispatches

Analysis of Student Sentiments towards the Use of Artificial Intelligence Intelligence in Educational Uses Naïve Bayes Algorithm

Primary research

#891

T1new
Topic
unassigned (set during synthesis)
First seen
2026-07-28 07:16:45
Last seen
2026-07-28 07:16:45

Source raw items (1)

  • Semantic Scholar2026-07-28 07:16:04
    Analysis of Student Sentiments towards the Use of Artificial Intelligence Intelligence in Educational Uses Naïve Bayes Algorithm

    The rapid development of Artificial Intelligence (AI) has significantly transformed the field of education. Generative AI applications such as ChatGPT, Gemini, and Microsoft Copilot are increasingly utilized by students to obtain information, assist in completing academic tasks, and improve learning effectiveness. This study aims to analyze students' sentiment toward the use of AI in education using the Naïve Bayes algorithm. Data were collected through questionnaires distributed to high school students in Palu City, Central Sulawesi Province, and processed through text preprocessing stages, including case folding, tokenization, stopword removal, and stemming. The dataset was divided into training and testing data to evaluate the model using a confusion matrix, accuracy, precision, recall, and F1-score. The findings indicate that the Naïve Bayes algorithm performs well in classifying students' sentiments toward AI in education. Most students expressed neutral sentiments regarding the use of AI in learning, while others reported positive and negative perceptions related to its benefits and potential risks. This study provides empirical insights into students' perceptions of AI in education and may serve as a reference for technology-based learning strategies. Students are encouraged to use AI wisely while maintaining critical thinking, analytical skills, and independent learning.