How to Tackle All 3 Parts of the Emerging Technology Assignment
Five technologies. Three assignment sections. A rubric that wants specific examples, real equity considerations, named challenges, and SWS-formatted citations. Here’s how to approach each part without producing a surface-level overview that reads like a Wikipedia summary.
Three parts. Five technology options. And a rubric that expects you to do more than describe what AI or AR is — it wants you to connect the technology to real classroom implications, name specific benefits and trade-offs, and think critically about where things are headed. The students who score well on this aren’t the ones who write the longest summaries. They’re the ones who pick a focused angle and support every claim with a source.
What This Guide Covers
Assignment Requirements at a Glance
Before picking a technology, map out what the rubric is actually asking. Three parts, each with multiple sub-points. Part 1 wants five distinct angles on effects (teaching, learning, engagement, motivation, accessibility, equity). Part 2 wants benefits and named challenges. Part 3 wants forward-looking reflection with ethical dimensions included. Two to three SWS citations across the whole piece.
Assignment Checklist
Choosing Your Technology: What to Consider First
Pick based on research availability, not familiarity. If you choose a technology you can’t find recent peer-reviewed studies for, all three parts of your assignment will be harder to support. AI in education currently has the largest body of published research — journals like Computers & Education and Educational Technology Research and Development have substantial recent coverage. Adaptive Learning Systems are a close second.
Before finalising your technology choice, run a quick search on Google Scholar or your institution’s database. Search your chosen technology + “education” + the current year range (2020–2026). If you find at least three peer-reviewed articles in the first two pages of results, you have enough to work with. If the results are thin, pivot to AI or Adaptive Learning, where the literature is much richer.
| Technology | Strongest Assignment Angle | Key Challenge to Address | Research Depth |
|---|---|---|---|
| Artificial Intelligence | Personalized learning, automated feedback, adaptive assessments | Data privacy, algorithmic bias, equity of access | Extensive — multiple meta-analyses available |
| Augmented Reality | Visualization in STEM, virtual labs, spatial learning | Device costs, implementation complexity, teacher training | Good — growing rapidly since 2018 |
| Internet of Things | Smart classrooms, attendance automation, real-time data | Infrastructure costs, data security, surveillance concerns | Moderate — more technical than pedagogical literature |
| Adaptive Learning Systems | Differentiated instruction, learning analytics, outcomes improvement | Cost of platforms, teacher displacement concerns, data use | Strong — especially K-12 and higher ed research |
| Game-Based Learning | Engagement, intrinsic motivation, critical thinking | Curriculum alignment, screen time concerns, equity of hardware | Good — solid engagement and motivation literature |
Part 1: How to Analyze the Effects on Education
This part has six distinct lenses: teaching processes, learning processes, student engagement, student motivation, accessibility, and equity/inclusivity. Don’t blend them into one paragraph. Each one is a separate analytical point and needs its own example.
Connect the Technology to a Specific Outcome — Not Just a Feature
Saying “AI can personalize learning” is a description. Saying “AI-driven platforms like Khan Academy’s adaptive system adjust problem difficulty in real time based on student error patterns, allowing teachers to redirect instructional time toward students who need direct intervention” is analysis. The difference is specificity and the connection to an educational outcome.
For every lens: Name what the technology does → describe the mechanism or example → state the educational effect → acknowledge any limitation or nuance. That structure covers both the positive impact and the critical thinking the rubric expects.How Does It Change What Teachers Do?
Does it automate routine tasks (grading, progress tracking)? Does it shift the teacher’s role toward facilitation or mentoring? Name a specific function and its classroom implication.
How Does Students Actually Learn Differently?
Does the technology allow self-paced progression? Immediate feedback? Multimodal content delivery? Ground this in a research finding, not a marketing claim from an edtech company.
Active vs. Passive Participation
Engagement isn’t just attention — it’s behavioral, cognitive, and emotional. How does your chosen technology affect each dimension? Game-based learning and AR tend to score well here; passive video watching does not.
Intrinsic vs. Extrinsic Drivers
Does the technology build intrinsic motivation (curiosity, mastery) or rely on extrinsic rewards (badges, leaderboards)? Self-determination theory is a useful framework here — it shows up in the EdTech literature frequently.
Who Gets Access to What?
Does the technology expand access to educational resources for students with disabilities, rural learners, or those in under-resourced schools? Or does it require hardware and bandwidth that creates new access barriers?
The Harder Question
This is where most assignments get shallow. The equity lens asks: who benefits and who doesn’t — and why? Algorithmic bias in AI systems, the digital divide in IoT, the cost of AR devices — each technology has an equity dimension that needs honest treatment.
Statements like “technology can help all students” don’t address equity — they sidestep it. The rubric specifically asks about potential implications for equity and inclusivity. That means you need to name who might be left out and why. A 2021 study in Computers & Education found that AI-powered tutoring systems showed differential performance gains across student demographic groups, partly tied to the quality of training data. That kind of nuance is what the rubric is looking for — not optimistic generalities.
Part 2: Benefits and Challenges of Integration
Two sides. Each needs to be specific. The rubric lists five named challenges: cost, complexity of implementation, data privacy, ethical concerns, and training requirements. Don’t skip any that apply to your chosen technology. A strong Part 2 addresses at least three of these challenges directly and names the benefit on the other side of each trade-off.
Writing the Benefits Section
Each benefit needs to connect to a real educational outcome — not just a capability. The benefit of AI automated feedback isn’t that it’s fast; it’s that immediate, specific feedback accelerates the learning cycle and reduces teacher workload so more time goes to direct instruction. Frame every benefit in terms of what it produces for learners or educators.
- Tie the benefit to a specific learning or teaching outcome
- Use a research finding to support it, not a vendor claim
- Don’t list benefits without explaining the mechanism
- One or two well-supported benefits beats a long generic list
Writing the Challenges Section
Work through each rubric-listed challenge and evaluate whether it applies to your technology. Cost is almost always relevant. Data privacy is critical for AI and adaptive systems. Training requirements affect all five technologies to varying degrees.
- Cost: device costs, platform licensing, infrastructure
- Complexity: integration with existing curriculum and systems
- Data privacy: student data collection, FERPA, COPPA implications
- Ethics: bias, surveillance, replacement of human judgment
- Training: teacher professional development requirements
This Applies to Almost Every Technology on the List
AI collects behavioral and performance data. Adaptive learning platforms track learning patterns over time. IoT devices in classrooms may collect location and activity data. AR apps often require camera access. For any of these, your challenges section should address what data is collected, who has access to it, and what regulations govern its use in K-12 and higher education settings (FERPA in the US is the starting point; COPPA applies to students under 13).
Don’t just mention data privacy — explain the specific risk for your technology and what mitigation looks like. That’s what separates a thorough Part 2 from a surface-level one.For each benefit: Name it → explain the mechanism → cite the evidence. For each challenge: Name it → explain the specific manifestation for your technology → note what mitigations or open questions exist. Symmetrical treatment makes the analysis more credible and shows you’re thinking critically, not just listing talking points.
Part 3: Future Implications — What to Actually Reflect On
This part asks four things: how the technology may evolve, how it will shape educational practices and preferences, how it will shape learning environments, and how it will affect the educator’s role. Then: opportunities and ethical concerns from wider adoption. Each of these is a sub-point — not one continuous narrative.
Ground Speculation in Current Trajectory, Not Science Fiction
The best reflections in Part 3 don’t predict a utopian or dystopian future — they trace the current direction of the technology and reason forward. If AI tutoring systems are currently achieving comparable outcomes to human tutors in narrow subject areas (which some research suggests), what does that trajectory mean for classroom structures in ten years? That’s grounded reflection, not guesswork. Use your sources to anchor the speculation.
Avoid: Vague statements like “technology will continue to evolve and shape education.” That says nothing. Instead: name the specific trajectory, name the specific implication, and name the tension or opportunity it creates.Where Is It Actually Going?
For AI: multimodal models, real-time translation, emotional detection. For AR: lighter hardware, spatial computing (Apple Vision Pro trajectory). Ground this in current R&D trends, not general optimism.
What Changes in How Schools Operate?
Does the technology enable hybrid models? Competency-based progression? Unbundled curriculum delivery? Think about structural shifts, not just new tools added to existing classrooms.
Physical Space and Virtual Space
Does the technology blur the line between classroom and home? Between real and simulated environments? IoT and AR in particular reshape what a “learning environment” even means physically.
Shift, Not Elimination
Research consistently shows technology augments rather than replaces effective teaching. But the role does shift — toward facilitation, relationship-building, and higher-order coaching. Be specific about what changes and what doesn’t.
What Becomes Possible?
Global equity of access to quality instruction, scaling of individualized support, data-driven early intervention for at-risk students. Name the specific opportunity and the conditions needed to realize it.
What Could Go Wrong With Wider Adoption?
Over-reliance on algorithmic decisions, erosion of teacher professional judgment, commodification of learning data, widening digital divides. Each of these has a literature base. Pick the one most relevant to your technology.
SWS Citation Format: What It Looks Like in Practice
SWS (Strayer Writing Standards) uses an author-date in-text citation format similar to APA but with some formatting differences. Check your course handout for the exact required format — SWS has been updated across different Strayer course cohorts and your program’s version is authoritative. Here’s the general structure:
In-Text Citation Format
Author’s last name and year in parentheses after the claim. If quoting directly, add the page number.
- One author: (Holmes, 2023)
- Two authors: (Holmes and Smith, 2023)
- Three or more: (Holmes et al., 2023)
- Direct quote: (Holmes, 2023, p. 47)
Reference List Entry — Journal Article
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Buckingham Shum, S., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., and Koedinger, K. R. 2022. “Ethics of AI in Education: Towards a Community-Wide Agenda.” Journal of Learning Analytics 9(1): 1–23.
SWS and APA look similar at the in-text citation level but differ in reference list formatting (punctuation, italicization, and ordering conventions). If your assignment says SWS format, use your course’s SWS guide, not an APA generator. Submitting APA-formatted citations for an SWS assignment will cost you formatting marks even if the content is right.
Where to Find Peer-Reviewed Sources for This Assignment
Two to three sources minimum. For an assignment this focused, peer-reviewed journal articles work better than books — they’re more recent, more specific, and easier to cite a specific finding from. Here’s where to look.
Databases to Search
- ERIC — education-specific, free with full text for many articles
- JSTOR — broad coverage of education journals
- Google Scholar — free, links to open-access versions
- Your institution’s library portal — access to Computers & Education, BJET
Key Journals to Target
- Computers & Education
- British Journal of Educational Technology
- Educational Technology Research and Development
- Journal of Learning Analytics
- Internet and Higher Education
Search Strategy
- Use quotes for exact terms: “artificial intelligence” AND “higher education”
- Filter by year: 2019–2026 for relevance
- Filter for peer-reviewed / scholarly articles
- Check the “cited by” count on Google Scholar — higher means more field influence
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Buckingham Shum, S., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., and Koedinger, K. R. (2022). “Ethics of AI in Education: Towards a Community-Wide Agenda.” Journal of Learning Analytics, 9(1), 1–23. Available at: https://doi.org/10.18608/jla.2022.7911. This peer-reviewed article directly covers AI in education with an equity and ethics lens — useful for Part 1 (equity), Part 2 (ethical challenges), and Part 3 (ethical concerns from wider adoption). It covers all three assignment parts from a single source.
Mistakes That Get Points Deducted
Describing the Technology Instead of Analyzing Effects
A paragraph explaining what AI is doesn’t address Part 1. The rubric asks for effects on education — outcomes, implications, changes to practice. Description without analysis reads like a product summary, not an academic assignment.
Lead With the Effect, Then Explain the Mechanism
Start with the educational outcome: “AI-driven formative assessment tools have been shown to reduce achievement gaps in introductory math courses by providing immediate, differentiated feedback” — then explain how. The effect comes first.
Skipping the Equity and Ethics Dimensions
Every technology on the list has an equity dimension. Ignoring it — or writing one optimistic sentence — leaves Part 1 incomplete and Part 3 superficial. The rubric explicitly lists equity, inclusivity, and ethical concerns as required content.
Name Specific Equity Risks and Mitigation Directions
For AI: algorithmic bias tied to training data. For AR: device cost as an access barrier. For IoT: data surveillance implications for lower-income school districts with less legal infrastructure. Be specific about who bears the cost of the challenge.
Generic Future Speculation Without Grounding
“Technology will continue to change education in the future.” This says nothing. Part 3 asks for reasoned reflection tied to the technology’s current trajectory and the specific implications for educators and learning environments.
Trace the Trajectory From Current Evidence
Use your sources to anchor the future reflection. If research shows AI tutoring systems currently match human tutors in narrow domains under specific conditions, reason forward: what structural changes does that enable, and what tensions does it create?
Citing Vendor Websites as Academic Sources
Khan Academy’s website, Duolingo’s blog, or an edtech company’s case study page are not peer-reviewed academic sources. SWS citations need to come from scholarly journals, books, or government/organizational reports with named authors.
Use ERIC, Google Scholar, or Your Library Database
Filter for peer-reviewed, 2019 onward. Journal articles in Computers & Education or British Journal of Educational Technology are the standard for this type of assignment. Two solid peer-reviewed articles and one government/policy report is a workable three-source strategy.
Frequently Asked Questions
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Education Assignment Help Get StartedThe Assignment Rewards Specificity, Not Length
This isn’t an assignment where more words automatically means a better grade. Part 1’s equity section written with a named research finding about algorithmic bias beats three generic paragraphs about how technology helps everyone. Part 2’s data privacy challenge written with a specific FERPA implication beats a vague sentence about “privacy concerns.”
Pick your technology early. Run a quick literature check. Then work through each rubric sub-point methodically — not as a continuous essay, but as six analytical points in Part 1, a benefits-and-challenges structure in Part 2, and four distinct reflective questions in Part 3. That structure makes it much harder to accidentally skip something the grader is looking for.
And on the SWS citations: format them correctly the first time. An incorrect citation format on two or three sources in a short assignment is a noticeable error. Check your course’s SWS guide, not a generic APA generator.