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Technology Supports for Scholars

A pick-your-path tour for early doctoral students

  1. Section 1 About Kendall 4 slidesVisited
  2. Section 2 What you told us 6 slidesVisited
  3. Section 3 How fast this is moving 10 slidesVisited
  4. Section 4 Google Scholar 9 slidesVisited
  5. Section 5 Content and context 6 slidesVisited
  6. Section 6 Using AI with care 7 slidesVisited

Click a tile or press 1 to 6. Arrow keys move through a section. Esc returns to this map. F toggles fullscreen.

Section 1 · About Kendall · Back to map

1.1

Where it started

The Tandy 1000 SX, 1987. 384K of memory, two floppy drives, $1,199 without a monitor
The Tandy 1000 SX, 1987. 384K of memory, two floppy drives, $1,199 without a monitor
  • Spent Saturday mornings on a TRS-80
  • Worked at Radio Shack through high school and college
  • Then a high school science teacher in Nebraska
  • Now Professor of Educational Technology at UNLV
1.2

Still a technology fan

With Leo Laporte on the set of This Week in Tech
With Leo Laporte on the set of This Week in Tech
  • Taught high school science in Bellevue, Nebraska, as Mosaic was introduced
  • Research on self-regulated learning, smartphones and learning, online learning, and generative AI in education
1.3

Generative AI and my work

  • I use these tools most days for writing support, data work, coding, website development, and course design
  • I study how to best use technology, and AI in particular, to help people learn
  • My default is curious and cautious
  • Don't mistake what I say for department, college, or university policy
1.4

How to use today

Section 2 · What you told us · Back to map

2.1

Who answered

  • 16 of you completed the survey
  • Most of you are in coursework, a few are preparing for comprehensive exams
2.2

What you already use

Number of respondents (of 16)

Google Scholar10ChatGPT9Gemini9Claude6A citation manager (Zotero, Mendeley, or EndNote)4A research-specific AI tool (Elicit, Consensus, Undermind)2

TakeawayGeneral chatbots are already common. Citation managers and research-specific AI tools are not.

2.3

Where your time goes

"Where do you lose the most time? Pick up to two." (Most of you picked more than two things.)

Reading articles13Keeping track of what I have read8Finding articles7Formatting citations7Synthesizing across studies5Staring at a blank page4

TakeawayReading is the bottleneck for nearly everyone. Remembering what you read is next.

2.4

What you want to learn about

"How interested are you in each? (1 = not interested, 5 = very interested)" (Average of your ratings.)

Google Scholar power tips4.1Managing many sources (NotebookLM, multiple PDFs)4.1Citation managers3.9AI and sensitive data3.5AI research tools3.5AI-made graphic organizers and tables3.4Building apps3.1
  • Other requests, paraphrased: AI workflows and prompting, Zotero and its link to Obsidian, non-AI analysis tools

TakeawayThe top two became the two deep dives. Citation managers and sensitive data show up in the last section.

2.5

How comfortable you are using AI in scholarly work

Number of respondents at each level (1 = not at all, 5 = very)

024681031228314251 = not at all, 5 = veryRespondents

TakeawayAverage 2.8. High interest, low comfort.

2.6

In your words (paraphrased)

  • I am not sure what my field thinks about AI
  • I worry I will use it the wrong way and get in trouble
  • I want to know the appropriate ways to use it
  • I have concerns about academic integrity
  • The water and energy cost makes me hesitant
  • Sometimes it says it did the work when it did not
  • I annotate articles but have no good system to find that knowledge later
  • I would like to connect Zotero with Obsidian

Section 3 · How fast this is moving · Back to map

3.1

Technology Adoption Curves

  • From the home computer to generative AI, 1984 to 2026
  • Kendall Hartley, Department of Teaching and Learning, University of Nevada, Las Vegas
3.2

Where we started, the original table

Households with a computer and Internet use, plus smartphone ownership, 1984 to 2021 (percent).

YearComputer at homeInternet at homeSmartphone
19848.2
198915.0
199322.9
199736.618.0
200051.041.5
200156.350.4
200361.854.7
200769.761.7
200974.168.7
201076.771.1
201175.671.735
201278.974.846
201351
201455
201586.876.767
201672
201877
201992.986.481
202185
0%25%50%75%100%19841990200020102020Computer at home, 1984: 8.2%Computer at home, 1989: 15%Computer at home, 1993: 22.9%Computer at home, 1997: 36.6%Computer at home, 2000: 51%Computer at home, 2001: 56.3%Computer at home, 2003: 61.8%Computer at home, 2007: 69.7%Computer at home, 2009: 74.1%Computer at home, 2010: 76.7%Computer at home, 2011: 75.6%Computer at home, 2012: 78.9%Computer at home, 2015: 86.8%Computer at home, 2019: 92.9%Internet at home, 1997: 18%Internet at home, 2000: 41.5%Internet at home, 2001: 50.4%Internet at home, 2003: 54.7%Internet at home, 2007: 61.7%Internet at home, 2009: 68.7%Internet at home, 2010: 71.1%Internet at home, 2011: 71.7%Internet at home, 2012: 74.8%Internet at home, 2015: 76.7%Internet at home, 2019: 86.4%Smartphone, 2011: 35%Smartphone, 2012: 46%Smartphone, 2013: 51%Smartphone, 2014: 55%Smartphone, 2015: 67%Smartphone, 2016: 72%Smartphone, 2018: 77%Smartphone, 2019: 81%Smartphone, 2021: 85%Computer at homeInternet at homeSmartphone

Source: U.S. Census Bureau, Current Population Survey, select years (computer and Internet), and Pew Research Center (smartphone). Values are percents.

3.3

Updated through 2026

Five more years of data and two new generative AI measures (new values shaded).

YearComputer at homeInternet at homeSmartphoneChatGPT use (Pew)Gen AI use (Fed)
201351
201455
201586.876.767
201689.381.472
201790.883.5
201891.885.177
201992.986.481
202195.090.185
202295.791.0
202396.192.19018
202496.693.2912344.6
2025913454.5
20264461.8

  New in the 2026 update. Rows before 2013 are unchanged from the original.

0%25%50%75%100%198419902000201020202026Computer at home, 1984: 8.2%Computer at home, 1989: 15%Computer at home, 1993: 22.9%Computer at home, 1997: 36.6%Computer at home, 2000: 51%Computer at home, 2001: 56.3%Computer at home, 2003: 61.8%Computer at home, 2007: 69.7%Computer at home, 2009: 74.1%Computer at home, 2010: 76.7%Computer at home, 2011: 75.6%Computer at home, 2012: 78.9%Computer at home, 2015: 86.8%Computer at home, 2016: 89.3%Computer at home, 2017: 90.8%Computer at home, 2018: 91.8%Computer at home, 2019: 92.9%Computer at home, 2021: 95%Computer at home, 2022: 95.7%Computer at home, 2023: 96.1%Computer at home, 2024: 96.6%Internet at home, 1997: 18%Internet at home, 2000: 41.5%Internet at home, 2001: 50.4%Internet at home, 2003: 54.7%Internet at home, 2007: 61.7%Internet at home, 2009: 68.7%Internet at home, 2010: 71.1%Internet at home, 2011: 71.7%Internet at home, 2012: 74.8%Internet at home, 2015: 76.7%Internet at home, 2016: 81.4%Internet at home, 2017: 83.5%Internet at home, 2018: 85.1%Internet at home, 2019: 86.4%Internet at home, 2021: 90.1%Internet at home, 2022: 91%Internet at home, 2023: 92.1%Internet at home, 2024: 93.2%Smartphone, 2011: 35%Smartphone, 2012: 46%Smartphone, 2013: 51%Smartphone, 2014: 55%Smartphone, 2015: 67%Smartphone, 2016: 72%Smartphone, 2018: 77%Smartphone, 2019: 81%Smartphone, 2021: 85%Smartphone, 2023: 90%Smartphone, 2024: 91%Smartphone, 2025: 91%ChatGPT use (Pew), 2023: 18%ChatGPT use (Pew), 2024: 23%ChatGPT use (Pew), 2025: 34%ChatGPT use (Pew), 2026: 44%Gen AI use (Fed), 2024: 44.6%Gen AI use (Fed), 2025: 54.5%Gen AI use (Fed), 2026: 61.8%Computer at homeInternet at homeSmartphoneChatGPT use (Pew)Gen AI use (Fed)

No Census estimates for 2020 or 2025 yet.

Source: U.S. Census Bureau (CPS to 2012, ACS 2015 to 2024), Pew Research Center, St. Louis Fed Real-Time Population Survey. Households for computer and Internet, adults for the rest.

3.4

Home computers, a 40-year climb

Households with a computer, from the Macintosh to today

0%25%50%75%100%198419902000201020202026Home computers, 1984: 8.2%Home computers, 1989: 15.0%Home computers, 1993: 22.9%Home computers, 1997: 36.6%Home computers, 2000: 51.0%Home computers, 2001: 56.3%Home computers, 2003: 61.8%Home computers, 2007: 69.7%Home computers, 2009: 74.1%Home computers, 2010: 76.7%Home computers, 2011: 75.6%Home computers, 2012: 78.9%Home computers, 2015: 86.8%Home computers, 2016: 89.3%Home computers, 2017: 90.8%Home computers, 2018: 91.8%Home computers, 2019: 92.9%Home computers, 2021: 95.0%Home computers, 2022: 95.7%Home computers, 2023: 96.1%Home computers, 2024: 96.6%96.6%Macintosh 1984Home computers
2.3
points per year, 1984 to 2024
16 years
from the Macintosh to half of households (2000)

In 1984 about 8% of households had a computer. It took until 2000 to pass half of households.

Dotted lines run from each key moment to the latest point on its curve. Households.

3.5

Home Internet climbs faster

Adding household Internet use, starting with the Mosaic browser

0%25%50%75%100%198419902000201020202026Home computers, 1984: 8.2%Home computers, 1989: 15.0%Home computers, 1993: 22.9%Home computers, 1997: 36.6%Home computers, 2000: 51.0%Home computers, 2001: 56.3%Home computers, 2003: 61.8%Home computers, 2007: 69.7%Home computers, 2009: 74.1%Home computers, 2010: 76.7%Home computers, 2011: 75.6%Home computers, 2012: 78.9%Home computers, 2015: 86.8%Home computers, 2016: 89.3%Home computers, 2017: 90.8%Home computers, 2018: 91.8%Home computers, 2019: 92.9%Home computers, 2021: 95.0%Home computers, 2022: 95.7%Home computers, 2023: 96.1%Home computers, 2024: 96.6%Home Internet, 1997: 18.0%Home Internet, 2000: 41.5%Home Internet, 2001: 50.4%Home Internet, 2003: 54.7%Home Internet, 2007: 61.7%Home Internet, 2009: 68.7%Home Internet, 2010: 71.1%Home Internet, 2011: 71.7%Home Internet, 2012: 74.8%Home Internet, 2015: 76.7%Home Internet, 2016: 81.4%Home Internet, 2017: 83.5%Home Internet, 2018: 85.1%Home Internet, 2019: 86.4%Home Internet, 2021: 90.1%Home Internet, 2022: 91.0%Home Internet, 2023: 92.1%Home Internet, 2024: 93.2%93.2%Macintosh 1984Mosaic browser 1993Home computersHome Internet
2.9
points per year, 1993 to 2024
8 years
from Mosaic to half of households (2001)

Mosaic appeared in 1993 and Netscape followed in 1994. Half of households were online by 2001.

Dotted lines run from each key moment to the latest point on its curve. Sources: U.S. Census Bureau, Pew Research Center, St. Louis Fed Real-Time Population Survey.

3.6

Smartphones compress the curve

Adding adult smartphone ownership, starting with the iPhone

0%25%50%75%100%198419902000201020202026Home computers, 1984: 8.2%Home computers, 1989: 15.0%Home computers, 1993: 22.9%Home computers, 1997: 36.6%Home computers, 2000: 51.0%Home computers, 2001: 56.3%Home computers, 2003: 61.8%Home computers, 2007: 69.7%Home computers, 2009: 74.1%Home computers, 2010: 76.7%Home computers, 2011: 75.6%Home computers, 2012: 78.9%Home computers, 2015: 86.8%Home computers, 2016: 89.3%Home computers, 2017: 90.8%Home computers, 2018: 91.8%Home computers, 2019: 92.9%Home computers, 2021: 95.0%Home computers, 2022: 95.7%Home computers, 2023: 96.1%Home computers, 2024: 96.6%Home Internet, 1997: 18.0%Home Internet, 2000: 41.5%Home Internet, 2001: 50.4%Home Internet, 2003: 54.7%Home Internet, 2007: 61.7%Home Internet, 2009: 68.7%Home Internet, 2010: 71.1%Home Internet, 2011: 71.7%Home Internet, 2012: 74.8%Home Internet, 2015: 76.7%Home Internet, 2016: 81.4%Home Internet, 2017: 83.5%Home Internet, 2018: 85.1%Home Internet, 2019: 86.4%Home Internet, 2021: 90.1%Home Internet, 2022: 91.0%Home Internet, 2023: 92.1%Home Internet, 2024: 93.2%Smartphones, 2011: 35.0%Smartphones, 2012: 46.0%Smartphones, 2013: 51.0%Smartphones, 2014: 55.0%Smartphones, 2015: 67.0%Smartphones, 2016: 72.0%Smartphones, 2018: 77.0%Smartphones, 2019: 81.0%Smartphones, 2021: 85.0%Smartphones, 2023: 90.0%Smartphones, 2024: 91.0%Smartphones, 2025: 91.0%91.0%Macintosh 1984Mosaic browser 1993iPhone 2007Home computersHome InternetSmartphones
4.9
points per year, 2007 to 2025
6 years
from the iPhone to half of adults (2013)

Social media followed a similar path. Adult use of any social media site went from 7% in 2005 to 50% in 2011, then leveled off near 72%.

Dotted lines run from each key moment to the latest point on its curve. Sources: U.S. Census Bureau, Pew Research Center, St. Louis Fed Real-Time Population Survey.

3.7

Generative AI, the steepest curve yet

Adding generative AI use, starting with the public release of ChatGPT

0%25%50%75%100%198419902000201020202026Home computers, 1984: 8.2%Home computers, 1989: 15.0%Home computers, 1993: 22.9%Home computers, 1997: 36.6%Home computers, 2000: 51.0%Home computers, 2001: 56.3%Home computers, 2003: 61.8%Home computers, 2007: 69.7%Home computers, 2009: 74.1%Home computers, 2010: 76.7%Home computers, 2011: 75.6%Home computers, 2012: 78.9%Home computers, 2015: 86.8%Home computers, 2016: 89.3%Home computers, 2017: 90.8%Home computers, 2018: 91.8%Home computers, 2019: 92.9%Home computers, 2021: 95.0%Home computers, 2022: 95.7%Home computers, 2023: 96.1%Home computers, 2024: 96.6%Home Internet, 1997: 18.0%Home Internet, 2000: 41.5%Home Internet, 2001: 50.4%Home Internet, 2003: 54.7%Home Internet, 2007: 61.7%Home Internet, 2009: 68.7%Home Internet, 2010: 71.1%Home Internet, 2011: 71.7%Home Internet, 2012: 74.8%Home Internet, 2015: 76.7%Home Internet, 2016: 81.4%Home Internet, 2017: 83.5%Home Internet, 2018: 85.1%Home Internet, 2019: 86.4%Home Internet, 2021: 90.1%Home Internet, 2022: 91.0%Home Internet, 2023: 92.1%Home Internet, 2024: 93.2%Smartphones, 2011: 35.0%Smartphones, 2012: 46.0%Smartphones, 2013: 51.0%Smartphones, 2014: 55.0%Smartphones, 2015: 67.0%Smartphones, 2016: 72.0%Smartphones, 2018: 77.0%Smartphones, 2019: 81.0%Smartphones, 2021: 85.0%Smartphones, 2023: 90.0%Smartphones, 2024: 91.0%Smartphones, 2025: 91.0%Generative AI (Fed), 2024: 44.6%Generative AI (Fed), 2025: 54.5%Generative AI (Fed), 2026: 61.8%61.8%ChatGPT, ever used (Pew), 2023: 18%ChatGPT, ever used (Pew), 2024: 23%ChatGPT, ever used (Pew), 2025: 34%ChatGPT, ever used (Pew), 2026: 44%44%Macintosh 1984Mosaic browser 1993iPhone 2007ChatGPT Nov. 2022Home computersHome InternetSmartphonesGenerative AI (Fed)ChatGPT, ever used (Pew)
14.7
points per year, 2022 to 2026 (St. Louis Fed)
3 years
from ChatGPT to half of working-age adults (2025)

Two measures: any generative AI use among adults 18 to 64 (St. Louis Fed), and ever used ChatGPT among all adults (Pew). Even the lower Pew line rises faster than home Internet did.

Dotted lines run from each key moment to the latest point on its curve. Sources: U.S. Census Bureau, Pew Research Center, St. Louis Fed Real-Time Population Survey.

3.8

Each new technology climbs faster

Average rise per year from the key moment to the latest data point.

0510152.3Computer(1984)2.9Internet(1993)4.9Smartphone(2007)14.7Generative AI(2022)Points per year
TechnologyKey momentYears to 50%
Home computer198416
Home Internet19938
Smartphone20076
Generative AI20223

The older technologies had decades to level off near 90% or more, which lowers their average slope. Years to 50% gives the same ordering.

Generative AI uses the St. Louis Fed series (adults 18 to 64). Sources: U.S. Census Bureau, Pew Research Center, St. Louis Fed Real-Time Population Survey.

3.9

How researchers spot AI writing

Marker words in PubMed abstracts, compared with their 2022 rate.

0x5x10x15x201520162017201820192020202120222023202420252026*Ratio to 2022 rateChatGPTdelve, 2015: 0.3xdelve, 2016: 0.3xdelve, 2017: 0.4xdelve, 2018: 0.4xdelve, 2019: 0.5xdelve, 2020: 0.6xdelve, 2021: 0.8xdelve, 2022: 1.0xdelve, 2023: 4.9xdelve, 2024: 17.3x17.3xdelve, 2025: 8.4xdelve, 2026 (Jan. to Sept.): 2.7xdelveunderscore, 2015: 0.8xunderscore, 2016: 0.9xunderscore, 2017: 0.9xunderscore, 2018: 0.9xunderscore, 2019: 0.9xunderscore, 2020: 0.9xunderscore, 2021: 1.0xunderscore, 2022: 1.0xunderscore, 2023: 2.1xunderscore, 2024: 8.8xunderscore, 2025: 14.9x14.9xunderscore, 2026 (Jan. to Sept.): 14.3xunderscoreintricate, 2015: 0.8xintricate, 2016: 0.8xintricate, 2017: 0.9xintricate, 2018: 0.9xintricate, 2019: 0.8xintricate, 2020: 0.9xintricate, 2021: 1.0xintricate, 2022: 1.0xintricate, 2023: 2.6xintricate, 2024: 7.3x7.3xintricate, 2025: 5.3xintricate, 2026 (Jan. to Sept.): 2.8xintricatepivotal, 2015: 0.8xpivotal, 2016: 0.9xpivotal, 2017: 0.9xpivotal, 2018: 0.9xpivotal, 2019: 0.9xpivotal, 2020: 1.0xpivotal, 2021: 1.0xpivotal, 2022: 1.0xpivotal, 2023: 1.3xpivotal, 2024: 3.1xpivotal, 2025: 3.2x3.2xpivotal, 2026 (Jan. to Sept.): 2.6xpivotalpatients, 2015: 0.9xpatients, 2016: 1.0xpatients, 2017: 1.0xpatients, 2018: 1.0xpatients, 2019: 1.0xpatients, 2020: 1.0xpatients, 2021: 1.0xpatients, 2022: 1.0xpatients, 2023: 1.0xpatients, 2024: 1.0xpatients, 2025: 1.0xpatients, 2026 (Jan. to Sept.): 0.9xpatients
17x
"delve" in 2024 compared with 2022
15x
"underscore" in 2025, and still near that level

"Delve" fell back after 2024 once it became a known tell. Detection studies now track hundreds of words at once.

Source: counts from PubMed (NCBI E-utilities), title or abstract, records with abstracts, retrieved Sept. 29, 2026. *2026 is January to September.

3.10

Inside scholarship, AI in biomedical papers

Share of PubMed Central papers showing signs of LLM-assisted writing.

0%25%50%75%100%2023202420252026Share of papersChatGPT, Nov. 2022Full papers, Mid-2023: 19%19%Full papers, Mid-2024: 52%52%Full papers, Mid-2025: 77%77%Full papers, Dec. 2025: 89%89%Full papersAbstracts, Mid-2023: 9%9%Abstracts, Mid-2024: 31%31%Abstracts, Mid-2025: 53%53%Abstracts, Dec. 2025: 68%68%Abstracts
89%
of full papers in Dec. 2025, up from 19% in 2023
1 in 40
papers with signs of AI use disclose it (all fields)

Estimates come from shifts in word use and cannot separate light editing from full generation. Still a preprint.

Source: Holzwarth, González-Márquez & Kobak, arXiv 2608.10715 (2026), points plotted at mid-year and Dec. 2025. Disclosure: He & Bu, PNAS (2026).

Section 4 · Google Scholar · Back to map

4.1

Initial settings

  • Sign in so My Library, alerts, Scholar Labs, and Quick Read work
  • Settings, Library links, add UNLV Libraries. Full-text links appear next to results
  • Settings, Bibliography manager, choose BibTeX or RefMan for one-click export to Zotero or another manager
  • Zotero Chrome plugin is invaluable
4.2

Search hacks

  • Advanced Search option
  • Left sidebar for a date range (Since 2022) and Review articles
  • Cited by moves forward to newer work that builds on a paper. Related articles finds close neighbors
  • All versions often turns up a free author copy
4.3

Journal rankings with Scholar Metrics

  1. Menu (top left), then Metrics
  2. Top publications ranks journals and conferences by h5-index
  3. Select View all
  4. Choose a category and subcategory, such as Social Sciences, then Educational Technology
  5. Search a journal by name to see where it sits
4.4

What the numbers mean

  • Higher means more cited, not necessarily better
  • Compare journals within a field, never across fields
4.5

Article rankings

  1. Click a journal's h5-index to see the articles that make it up, most cited first
  2. This is a quick way to find the papers everyone in a subfield is citing
  3. Cited by counts on any result give the same signal for a single article
  4. Sort what you find into must-read and skim
4.6

Author metrics and alerts

  • Author profiles show total citations, h-index, and i10-index, all time and for recent years
  • Follow an author to get new articles and new citations by email
  • Create alert on a search or on a key paper's citations
  • Start your own profile now
4.7

A caution on metrics

  • Scholar counts citations broadly (preprints, theses, slides), so its numbers run higher than Scopus or Web of Science
  • Citation counts measure attention, not quality
  • Ask your chair which journals matter in your area before using any ranking to choose where to submit
4.8

AI search inside Scholar

  • Scholar Labs takes a full research question in plain language, not keywords
  • It breaks the question into parts, searches Scholar, and returns papers with a short note on how each one answers the question
  • Quick Read (new in 2026) gives a structured summary of an article to help decide whether to read it
  • Both require signing in
4.9

Where AI search falls short

  • It returns a limited set of papers and does not support Boolean operators
  • Good for finding a starting set, not for a systematic review
  • A summary is not a reading. Open the article before you cite it

Section 5 · Content and context · Back to map

5.1

The problem you described

  • Reading takes the most time
  • Remembering what you read is the second problem
  • Notes end up spread across PDFs, folders, and apps
5.2

Context

  • Chats, folders, notebooks, and projects
  • A notebook built on sources you choose (PDFs, Google Docs, web pages, videos)
  • Answers come with citations that point to the passage in your source
  • Today's demo is NotebookLM (Google now also calls it Gemini Notebook)
  • Similar options at UNLV include Claude projects (free to UNLV students through Rebel Spark AI) and Gemini with uploaded files
5.3

NotebookLM in practice

  • One notebook per course, project, or comps question
  • Ask questions across all sources at once and click each citation to check it
  • Generate a study guide, briefing doc, or mind map from your sources
  • Audio overviews turn a set of readings into a podcast-style conversation
  • Free accounts allow up to 50 sources per notebook, each up to 500,000 words
  • Sign in with your UNLV Google account to possibly activate more sources
5.4

Questions that work well

  • What methods did these studies use, and what were the sample sizes?
  • Where do these authors disagree?
  • Which of these sources define construct, and how?
  • What does source 3 say about topic? Quote it.
  • Build a table comparing purpose, sample, and findings
5.5

A system for keeping what you read

  • Zotero holds the articles and your annotations
  • A notes app (Obsidian, Google Docs, or Notion) holds your own synthesis
  • A grounded AI notebook helps you search across both
  • Write Say a one-paragraph summary yourself (Wispr Flow, or use my referral link, which gets me a free month)
5.6

Where this goes wrong

  • It can miss a key point or blend two sources
  • It cannot tell you a study is weak
  • A summary is not a substitute for reading the articles you will cite
  • Use it to decide what to read closely and to find what you already read

Section 6 · Using AI with care · Back to map

6.1

Start with the rules that apply to you

  • Your syllabus and your instructor
  • Your committee and your chair
  • The journal or conference you submit to (most now have AI policies)
  • UNLV generative AI guidance for students and the Student Academic Integrity Policy (links in 6.7)
  • This is a fluid situation. Guidance tomorrow will likely look different than guidance today
6.2

Disclose and keep records

"During the preparation of this study, the authors used Claude 4.6 for the purposes of developing GenAITutor.net, which was the primary data collection and analysis system. Claude 4.8 was also used to critique methods, analysis, and conclusions and contributed to the final editing process. The authors have reviewed and edited the output and take full responsibility for the content of this publication."
6.3

Check everything it claims

  • Verify every citation. Look up the article yourself
  • Check that a quote actually appears in the source
  • If it says it read, ran, or saved something, confirm it did
  • Ask it to show its work and point to the source
  • Reviewers will punish hallucinations mercilessly
6.4

Sensitive data

  • Do not upload participant data, identifiable information, or student records to consumer AI tools
  • Your IRB protocol governs where research data can go
  • UNLV's rule is plain. Never enter FERPA or HIPAA protected data, or personal and sensitive information, into any AI tool, even one covered by a UNLV agreement
  • UNLV-supported tools (Claude, Gemini through Rebelmail, ChatGPT, Google AI Pro) keep chats out of model training and away from human review. That is better protection, not permission for sensitive data
  • A Freedom of Information Act request may make your prompts front page news
6.5

The cost question

6.6

Citation managers, quickly

  • Only 4 of 16 of you use one
  • Zotero is free, works with Word and Google Docs, and grabs citations from the browser
  • Pair it with Google Scholar search and the Zotero Chrome plugin
  • Zotero connects to Obsidian through community plugins