NCEA LEVEL 2

ICT Research

A practical guide to teaching AS 2.8 — 91105: Information and Communications Technology Research. This session covers topic selection, hypothesis formulation, AI-assisted questioning, and evidence integration.

Teenaa kooutou katoa

Ko Julie Lawson tookuu iingoa

Noo Ingarangi ahau

Kei Aka Aka ahau e noho ana

Ko au te kaiako reo Pākehā i te Kareti o Tuakau.

Four goals for today’s session:

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1. Support with engagement and topic selection

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• How to formulate a hypothesis for research

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• How to craft research questions

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• AI tools - how and when

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Resource sharing and questions

Engagement and Topic Selection - games

Vocabulary Seeking

A timed game to surface domain-specific language. Students compete to find the most precise terminology for their chosen topic.

Polysyllabic Excellence

Reward the most complex and obscure words. Complexity of vocabulary signals depth of research and conceptual understanding.

Categorising Terms

Map vocabulary to perspectives. Are there communities of shared values or opposing viewpoints emerging?

News Hunt

Where are the issues happening right now? Use current events as a stimulus to ground research in the real world.

Topics That Work — and Topics That Don't

The Golden Rule

Topics must be genuinely open — not black and white, but grey. If the answer is obvious, the research has nowhere to go.

Topics that have failed in practice:

• God is real
• Atlantis is real
• Redheads have no soul

The Solution

One period. One reliable expert source — Google Scholar or Academia — that supports their research direction.

If they can't find it, they can't have that topic.

This single checkpoint prevents weeks of wasted research on unsupportable claims.

Formulating Hypotheses

Strong hypotheses are open-ended, arguable, and researchable. These three sentence starters give students a reliable scaffold:

1

To what extent does…

Invites evaluation of degree rather than a simple yes/no. Naturally opens space for multiple perspectives.

2

Should there be a…

Frames the issue as a policy or ethical question. Requires students to weigh evidence and propose a position.

3

Does X affect Y?

Establishes a causal or correlational relationship. Clear variables make for focused, measurable research.

Forming Research Questions

Definitions

Stakeholder perspectives and oppositions

Recommendations

Changes and practical solutions

Scope

Statistics and groups affected

This three-question structure ensures students move from understanding the debate, to quantifying the impact, to proposing meaningful change — mirroring the assessment's analytical demands.

AI Opportunity: Students can use AI to generate draft questions from their hypothesis, then refine them with teacher guidance.

AI in Action: A Worked Example

The Student Prompt to Gemini

"My hypothesis is that water pollution is about corporate greed. I need to research this to prove or disprove my hypothesis, and make recommendations for change. As a Year 12 English student of NZ, can you craft me three questions that will help me to gain insights into this complex issue?"

AI-Generated Questions

Q1: Definitions & Oppositions

To what extent do different stakeholders agree or disagree on the primary causes of water pollution in New Zealand?

Q2: Statistics & Affected Groups

What data connects corporate activity to declines in water quality, and how has this impacted tangata whenua?

Q3: Changes & Recommendations

What frameworks have held corporations accountable globally, and how could these apply to New Zealand?

AI Follow-Up: Checking Research Viability

The Follow-Up Prompt

Students should ask: "Is there enough research to support these questions?"

"Absolutely. You will find an abundance of high-quality, credible websites to answer these questions, especially within the New Zealand context. Water quality is one of the most heavily debated and documented environmental issues in NZ."

Why This Matters

Critically, the AI did not provide direct links — it guided rather than completed the search.

This is the ideal outcome: students receive direction, not answers. They must still locate, evaluate, and engage with sources themselves.

Teach students to treat AI as a research compass, not a shortcut.

Weaving in Evidence

Introducing a Perspective

• "From the perspective of [Group], it is argued that…"
• "Representatives from [Organisation] contend that [Quote], suggesting that…"
• "As highlighted by [Author], the primary concern regarding this issue is…"

Counter argument Transitions

• "Conversely, [Opposing Group] challenges this view, asserting that…"
• "While some argue that [Idea A], alternative evidence suggests that…"
• "In contrast to the claims made by [Source A], [Source B] argues that…"

Integrating Data & Statistics

• "This argument is heavily supported by data from [Source], which reveals that…"
• "A clear correlation between [Variable A] and [Variable B] is evidenced by…"

Recommendations & Implications

• "Models from [Context] demonstrate that when [Action] is implemented, [Result] occurs."
• "The evidence implies that reforming current frameworks would create a systemic shift."

Support Resources

Here are the tools that I have used with my students.

Marking Schedule

Co-constructed from exemplars and explanatory notes. Shared with students from day one.

Current Events Research

The news as stimulus. Real-world issues spark genuine inquiry and authentic engagement.

Suggested Topics

A curated list of researchable, grey-area topics to help students who are stuck at the starting line.

Research Log & Checkpoints

A structured log to track progress and ensure students meet formative checkpoints before submission.