Card of the learning path

 
General topic of the learning path
 
Artificial Intelligence in Biotechnology
Specific name of the learning unit
 
AI-Powered Biotechnology: Unlocking New Possibilities in Drug Discovery
Age of the target users

14-18 target
Requirements for the learner
  1. 1.    Basic understanding of environmental science concepts (e.g.,ecosystem, climate).
    Basic literacy and numeracy skills.
    Basic ICT skills.
  2. Access to a computer or tablet with internet connectivity.
  3. Willingness to engage with digital tools (AR apps, CoSpaces Edu).
  4. No prior coding or AR development experience required, as CoBlocks is beginner-friendly.
Description of the learning unit This learning unit provides a comprehensive introduction to artificial Intelligence in biotechnology and more specifically to new possibilities in drug discovery. It is divided into three sections: "Explore" introduces foundational concepts of climate change, ecosystems, and restoration. "Execute" delves into bio-inspiration, showcasing how natural processes inspire solutions and how Augmented Reality (AR) can visualize these processes and impacts, supported by real-world examples and practical activities. "Enhance" justifies the pedagogical benefits of AR, offering examples of useful AR applications and practical integration strategies. The unit culminates in a hands-on exercise where students use a gamified AR experience in Delightex to strengthen their understanding and engagement with the topic. 
Subject: Parties involved Digital Literacy/Computer Science, Art & Design, Social Studies, Mathematics , Language Arts 
Keywords Artificial Intelligence (AI)
Biotechnology, Drug Discovery, Machine Learning (ML), Deep Learning, Target Identification, Virtual Screening, Clinical Trials Optimization, Drug Repurposing
Bio-inspiration, Digital Literacy, Augmented Reality (AR), Gamification.
Key qualifications, skills and knowledge that can be acquired

Skills:

  • Critical Thinking: Analyzing large datasets to identify patterns and make predictions in a scientific context.
  • Problem-Solving: Applying bio-inspired concepts to drug discovery challenges, such as matching drug candidates to targets.
  • Digital Literacy: Navigating and utilizing AR applications.
  • Scientific Inquiry: Interpreting data and observing natural processes (virtual or real).
  • Communication: Explaining complex concepts and presenting ideas.

Knowledge:

  • Understanding of core principles of biotechnology and artificial intelligence (AI), including Machine Learning (ML) and Deep Learning.
  • Understanding how AI is integrated into various stages of drug development, from target identification and virtual screening to clinical trials and drug repurposing.
  • Recognising bio-inspired solutions derived from nature.
  • Understanding the potential and applications of Augmented Reality in Bio-sciences and Health Sciences
Resources and didactic aids used
  • Textbooks/Scientific articles
  • Case studies
  • Internet resources
  • Free AR platforms (Delightex)
  • AR-compatible devices (smartphones/tablets)
Assessment criteria and evaluation
  • Participation: Engagement in discussions and activities throughout the unit.
  • Activity Completion: Execution of practical AR exercise
  • Concept Map/Mind Map: Creation of a visual representation linking climate change, ecosystems, restoration methods, and bio-inspired solutions.