A study note on dynamic, independent and critical thinking in AI usage by students

A study note on dynamic, independent and critical thinking in AI usage by students (MBA and Housing Studies) (information from perplexity.ai)

My question 1: "What are dynamic, independent and critical thinking in AI usage in the context of students' learning in MBA and Housing Studies Degree study?"

The reply: "Dynamic, Independent, and Critical Thinking in AI Usage for MBA and Housing Studies Students

Dynamic Thinking

Dynamic thinking in the context of AI usage refers to students' ability to adapt their learning strategies and decision-making processes in real-time, making use of the immediate feedback and scenario adjustments that AI-enabled tools provide. In MBA programs, AI-driven simulations allow students to experiment with different strategies in changing business environments, seeing instant results and adjusting their approaches accordingly. This hands-on experience promotes adaptability and resilience—key qualities for future business leaders. For Housing Studies, dynamic, AI-powered platforms enable students to interactively design and assess housing concepts, providing multiple design alternatives and engaging students in an iterative, real-world design process.

Independent Thinking

Independent thinking means students use AI as a resource for information, discovery, or feedback, but retain agency over their own learning and decision-making. Rather than passively accepting AI-generated answers, students are encouraged to formulate their own analyses, judgments, and solutions. In MBA settings, there is concern that over-reliance on AI for assignments or case study solutions can hinder students’ ability to think independently and argue their points under pressure. Educators emphasize that AI's greatest value is as a "co-pilot," supporting exploration but not substituting for original analysis or insight. In Housing Studies, independent thinking is demonstrated when students use AI-generated data or models as a foundation but give critical consideration to context, user needs, and ethical implications, rather than relying on automated recommendations unquestioningly.

Critical Thinking

Critical thinking encompasses questioning assumptions, evaluating sources, assessing AI outputs critically, and recognizing the limitations and biases of any machine-generated suggestion. MBA programs increasingly highlight the importance of students challenging the validity of AI responses, probing deeper than surface-level results, and integrating AI into more nuanced human-centric decision-making processes such as stakeholder analysis and ethical debates. In Housing Studies, critical thinking is essential as students may use AI to model energy efficiency or user preferences, yet must synthesize these outputs with human factors, policy impacts, and sustainability goals. Critical thinking ensures students are not just consumers of AI-generated data but thoughtful evaluators and integrators of information for complex real-world challenges.

AI in Action: Integrated View

Aspect	MBA Programs	Housing Studies Degree
Dynamic Thinking	Real-time, AI-driven business simulations; adaptation to market changes and immediate consequence analysis	Interactive, generative design platforms; iterative planning and analysis involving real-world housing scenarios
Independent Thinking	AI as brainstorming or research assistant; students must defend and own their analyses rather than regurgitate AI outputs	Using AI-generated options/data as inputs, but contextualizing with stakeholder needs and policy/context-based reasoning
Critical Thinking	Probing AI-generated insights, questioning validity, recognizing biases, integrating ethics and strategic context	Examining interplay between technical solutions and human perceptions or sustainability outcomes

Key Takeaways

• Balanced AI Use: Effective learning involves using AI dynamically and interactively, but always paired with independent and critical thinking for the best educational outcomes in both MBA and Housing Studies programs.

• Risks of Over-reliance: Passive use of AI can lead to atrophied critical thinking and skill gaps. Students should be tasked with defending, debating, and contextualizing AI-driven results, not just accepting them at face value.

• Preparation for Real-world Challenges: Students who combine dynamic interaction with AI, independent interpretation, and critical evaluation are better equipped for modern professional environments where technology and human insight must work together.

This integrated approach aims to produce graduates who are adaptable, innovative, and critical in their use of technology, ready for leadership in data-driven and rapidly changing industries.

My question 2: "Is there a risk of worsening "academic inflation" if the MBA and Housing Studies students substantially and easily improve their academic performance with AI usage in doing assignments and dissertation projects?

The reply: "The risk of worsening "academic inflation"—where degrees lose their distinct value because more students achieve higher academic qualifications—does exist if MBA and Housing Studies students can substantially and easily enhance their performance using AI for assignments and dissertations.

When AI tools make knowledge and advanced capabilities rapidly accessible, the unique signaling power of a degree may diminish. This is because what used to require significant intellectual effort and mastery can now often be achieved through AI-driven automation: generating reports, analyses, or even dissertation drafts rapidly and at scale. As a result, the economic "premium" attached to many degrees is now under pressure, with employers reevaluating what academic credentials really demonstrate about a graduate’s skills and capabilities.

Students and educators themselves have voiced concerns that if assignments do not adapt and assessment criteria remain unchanged in the AI era, the real learning and development may not reflect the grades awarded—leading to possible dilution of program reputation and value. For example, MBA students at leading programs have reported that current curricula and assessments are sometimes mismatched to the capabilities of AI, making it possible to achieve high marks without actually building meaningful skills.

This aligns with broader scholarship on academic inflation, which notes that as more people attain higher qualifications—whether through easier access or automated means—the bar for what counts as "distinction" rises, and employers may start requiring even higher credentials for jobs that used to require less, compounding the inflation problem.

In summary:

• AI can lower the barriers to high academic performance, risking the inflation and devaluation of traditional credentials.

• If degrees are seen as easier to obtain due to AI assistance, their signaling value in the job market drops.

• The solution lies in evolving assessment methods, curriculum design, and focusing on the skills—like independent, critical, and dynamic thinking—that AI cannot easily replicate.

Educators must ensure that learning outcomes and assessments challenge students beyond what AI can automate, to preserve the integrity and value of their programs in a changing educational landscape".

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