Screenshot of my comment on team members posts
Reflection 2: Perplexity as an AI tool
Overview of Perplexity
For module 2 blog i chose to use Perplexity. I have never heard or seen this AI tool before so I was curious about it. I have used other LLMs before like ChatGPT for statistic courses, suggestions and other things. Perplexity is very similar to ChatGPT in the sense that it searches the internet to give as accurate as possible answers to prompts.
What I noticed about Perplexity is the easy to use interface, it looks more inviting than ChatGPT. I also noticed with the prompt I imputed it gave a more detailed response and delivered it in a nice readable way instead of just a block of answers. I found that it would go the extra mile to provide extra information that can be helpful even though it is not directly related to the question. This can be very helpful when doing research, or being used in educational settings.
TPAK Analysis of Perplexity’s Function – Prompted from ChatGPT
Technological Knowledge (TK)
- Perplexity.ai uses advanced natural language processing (NLP) and machine learning to deliver precise answers from the vast internet. Its interface allows users to ask questions naturally and receive real-time responses from different content sources.
- Technological Strengths:
- Efficiency: Quick, relevant results are generated using AI models.
- Intuitive Interface: Natural language processing makes it user-friendly.
- Adaptability: Learners can access a variety of information types (text, summaries, contextual answers) quickly.
- Weaknesses: Limited control over search depth or reliability of sources. Over-reliance on AI-generated answers can bypass critical engagement with content.
Pedagogical Knowledge (PK)
- Pedagogical Implications: Educators can leverage Perplexity.ai to help students develop critical thinking, research skills, and information literacy.
- Strengths:
- Active Learning: Students can independently search for answers, promoting inquiry-based learning.
- Collaborative Learning: Can be used for group work where students compare AI-generated responses, fostering discussion.
- Teacher Support: Saves time for educators by summarizing information quickly, freeing them to focus on deeper teaching objectives.
- Weaknesses: Without proper guidance, students may over-rely on the AI’s output, diminishing deeper engagement with learning processes or ignoring critical evaluation of sources.
- Strengths:
Content Knowledge (CK)
- Perplexity.ai taps into a vast amount of online data, including academic content, real-world news, and popular culture.
- Strengths:
- Broad Content Coverage: It pulls from multiple sources, providing varied perspectives.
- Relevant Information: Generates concise summaries tailored to specific queries, which can be directly relevant to the curriculum.
- Weaknesses: Not all content retrieved will be accurate or academically rigorous. Its responses might not cover in-depth or highly specialized content.
- Strengths:
TPACK Intersection (Technological Pedagogical Content Knowledge):
Perplexity.ai fits the TPACK framework by blending technology, pedagogy, and content. It offers a tool that can enhance learning if used correctly:
- Technological & Content (TCK): The AI enables access to vast content, but educators need to ensure it aligns with curricular goals and is critically assessed.
- Technological & Pedagogical (TPK): Perplexity.ai offers flexible pedagogical approaches (self-directed learning, inquiry-based models), but the educator’s role is crucial in guiding its use.
- Pedagogical & Content (PCK): Teachers must be aware of how the AI-generated content fits into the broader learning objectives and how it helps students build knowledge, not just retrieve answers.
In conclusion, Perplexity.ai is a powerful tool that, when integrated thoughtfully, can enhance teaching and learning experiences. Educators must, however, ensure it is used in a way that encourages deeper thinking, accurate content comprehension, and technology literacy, ensuring a balance among technological, pedagogical, and content knowledge to meet educational goals.
References
“create a TPACK analysis of perplexity.ai AI search engine functions” prompt ChatGPT, 11 Oct. 2024, OpenAI, https://chatgpt.com/.
Famure, Princess. Screenshot of Perplexity.ai interface. 11 Oct. 2024. Author’s personal photos.
Using Screencasting for Multimedia
Mayer’s Principle in Multimedia Learning
Mayer’s Cognitive Theory of Multimedia Learning, developed by psychologist Richard E. Mayer, explains how people learn more effectively from multimedia presentations, which combine text, images, audio, and animations.
The principles that seemed most intuitive to me was the signaling principle; which involves using headings and visual cues to direct attention to key elements. It naturally guides the learner to focus on important information, reducing cognitive strain. The principle that surprised me the most was modality principle, the suggestion that narration combined with images is more effective than labels with images was surprising. It challenges the common assumption that written text is essential for reinforcement.
CapCut Hidden Gem
In my screencasting video, I explain how to create a simple menu poster using CapCut software and how it can be used for other purposes other than video editing. I integrated coherence Principle aiming to keep my screencast free of unnecessary distractions and focused on the key learning points.
When making my video, my main focus was was an audience new to capcut, I focused on simplifying complex concepts (managing Intrinsic Load) and pacing the material to make it digestible. For example, breaking down ideas into manageable chunks (Segmenting).
In the past i have implemented the redundancy principle trying to avoid overwhelming learners by not repeating information in both text and narration in past presentations. I am however guilty of the modality principle overusing text on slides alongside narration, potentially overloading the verbal channel. Going off of that, I would try and focus on leveraging modality more effectively by integrating narration with visuals and minimizing text. Additionally, try to explore how personalization can make your multimedia more engaging and learner-friendly.