This article serves as a sequel to Part I and aims to assist educators in steering research projects that creatively integrate artificial intelligence applications. The objective is to make scholarly endeavors more engaging and pertinent for today's high school students, often referred to as the Alpha generation.
The underlying premise is that robots won't supplant us. Rather, as the educational vanguards of this era, it's imperative that we identify innovative ways to leverage robotics for various tasks that enhance human life. After all, the spirit of exploration is intrinsic to our human nature.
From the invention of the wheel to present-day advancements, humanity has consistently demonstrated its capacity for groundbreaking knowledge and creativity. Each generation manages to challenge the status quo in multifaceted ways, as you can read more about in our site's news channel.
While the notion of a self-exploring robot may still be far-fetched, it's human curiosity that fuels progress. Our students are coming of age in this dynamic landscape, and it's our responsibility to equip them for the realities they will face.
Curiosity is the engine of research. To immerse our students in the 'researcher's lifestyle' within the classroom, we need to guide them through a series of steps:
Develop a compelling question that doesn't have a straightforward answer.
Dive deep into the subject matter from credible sources to evaluate their relevance and identify gaps in existing research. This step is crucial for refining the initial question and forming research hypotheses.
I covered these first two steps in Part 1 of this series. Now, let's move on to the remaining steps:
3. Gather field data through interviews, online research, and observations, depending on the research question and field.
4. Process and analyze this data iteratively, refining sub-questions and testing hypotheses.
5. Answer the research question while adhering to scientific research standards.
6. Compose the research report, citing sources and following field-specific guidelines.
Be open to critique and use it to improve and plan future research endeavors.
Here are some more detail for further practice to revolutionize research processes with AI tools today:
3. Gather field data through interviews, online research, and observations, depending on the research question and field.
Once students have a well-defined research question and a solid understanding of the topic, we can assist them in data collection and analysis.
The thrill lies in the journey to the field!
Various research methods and tools extend beyond the scope of this brief post.
So, I'll share two examples to inspire the integration of creative AI tools in your guided research:
Example 1: Utilizing existing online databases and analyzing them with AI tools offers the advantage of rapid, large-scale data processing. AI excels in trend identification, a skill invaluable to future researchers. I highly recommend exposing students to current AI applications in various research fields.
As for the tools, I used the Cloud 2 application, developed by the same engineers behind Chat GPT. I chose it for its Hebrew language support and file-upload capabilities without requiring additional plugins. Note: If you're installing it, you may need to use a VPN set to the USA or England.
The pace of change is rapid, so stay tuned for updates!
I accessed the cbs.gov.il to obtain data tables for this experiment. It's crucial for students to anonymize participant information when gathering data through questionnaires, given the privacy concerns associated with AI tools, which learn from the data inputted.
I uploaded the file to the Claude application and began querying it.
For advanced students, you can pose research questions (as outlined in the first section of Post one) and refer to the research hypotheses (from the second section in Post one).
For instance, you can instruct the AI to identify data relevant to your research question or to confirm or refute hypotheses based on the data provided. This is an excellent opportunity to teach students how to distill broad questions into more focused queries.
Caution: Ensure there's ample data for analysis; otherwise, the AI may produce misleading results. Encourage students to critically evaluate the answers they receive.
The second example involves collecting data through surveys distributed via social media. AI tools can help craft compelling social media posts to encourage participation. For instance, if I'm studying teenage dietary habits and wish to circulate a survey, I can seek assistance from the chatbot, as demonstrated in the following video-
In the video, for the sake of brevity, I didn't engage the AI in a dialogue to explore alternative responses. However, it's highly recommended to iterate with the chatbot to refine the output before dissemination.
You may have noticed that I didn't type my queries; instead, I spoke them. A pro tip for those who'd like to dictate to the machine is to use a Chrome extension called TalkBerry. You can activate it in your preferred language directly within the ChatGPT interface, just above the text input field. While the voice output may sound a bit robotic, it's a useful feature for both accessibility and convenience.
Furthermore, the data gathered from student-distributed surveys can later be imported into chat tools for analytical assistance, as previously illustrated in the first example.
4. Addressing the Research Question
Crafting paragraphs that answer the research question, based on data collected from databases or surveys, is a labor-intensive task requiring deep analytical and conceptual skills. Students should skillfully integrate the information they've reviewed in step 2 with the data collected and analyzed in step 3. Encourage them to write and analyze these paragraphs themselves, as this is a crucial part of the learning journey.
You can then consult the chatbot to identify logical gaps or to refine the language for academic writing. Text can be uploaded to Cloud 2 for feedback. If you provide a slider tool, the machine can offer suggestions for improvement.
On a personal note, writing my PhD involved multiple drafts, a process that can now be streamlined with the help of AI, saving valuable time for educators.
5. Crafting the Research Report
Adhering to the specific writing style of the academic field is essential. At this stage, the chatbot can serve as a writing coach, offering feedback based on field-specific rules.
Idea A: Use examples of excellent and subpar research papers to train the machine. Engage in conversations with the AI to derive insights that can be used as evaluation metrics for new submissions.
Idea B: Discuss key performance indicators with students and tailor them to the type of work being written. Draft a prompt to train the machine into a personalized writing advisor. Always continue the chat in the same sequence to maintain context.
6. Peer Review and Self-Awareness
Encourage students to use research-oriented platforms like Perplexity.ai for peer review. Since the machine is perceived as neutral, students may be more open to its feedback.
It's crucial to note that all these are initial experiences and merely suggestions. The implementation is up to each educator, in collaboration with their students.
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Best wishes to all 21st-century educators!