# data[].attributes.headline
How does formal training in prompt engineering techniques affect information-seeking behaviors, search efficiency, and the quality of retrieved information among undergraduate researchers?

# data[].attributes.subject
How does formal training in prompt engineering techniques affect information-seeking behaviors, search efficiency, and the quality of retrieved information among undergraduate researchers?

# data[].attributes.body
TITLE-ABS-KEY(("prompt engineering" OR "AI prompting") OR
AND ("formal training")
AND ("information-seeking behavior" OR "search behavior" OR "research behavior")
AND ("search efficiency")
AND ("college student*" OR "undergraduate researcher*"))T

# data[].attributes.body
("prompt engineer*" OR "search method*" OR "search efficiency")

AND

("information-seeking" OR "information seeking")

AND

("search efficiency" OR "search quality")

AND

(undergrad* OR "undergraduate student*" OR "college student*") (0 results)

( ChatGPT OR "generative AI" OR "large language model*" OR "AI prompt*" ) AND ( "information seeking" OR "search behavior" OR "search strateg*" ) AND ( "search efficiency" OR "information quality" OR relevance ) AND ( undergrad* OR student* OR "college student*" ) 5 results

# data[].attributes.body
TS=("prompt engineering" OR "AI prompting" OR "LLM prompting" OR "generative AI")
AND

TS=("training" OR "instruction" OR "intervention")

AND
TS=("information seeking" OR "search behavior" OR "information literacy")
AND
TS=("undergraduate students" OR undergraduates OR "college students" OR "undergrads")

# data[].attributes.body
TITLE-ABS-KEY ( ( "formal training" OR "prompt engineering" OR "prompt design" OR "prompt techniques" ) AND ( "information-seeking" OR "search behavior" OR "search strategy" OR "information retrieval" ) AND ( efficiency OR quality ) AND ( undergraduate OR "undergraduate researchers" OR "university students" ) )

# data[].attributes.body
(TITLE-ABS(“information retrieval*” OR “prompt engineering*” OR “ai literacy* OR "artificial intelligence*” OR “prompt training*” OR “formal training*” OR “chain of thought prompting*” OR “tree of thought prompting*” OR “prompt refinement*” OR “generative ai*” OR engineering technique*”) AND (“undergraduate*” OR “undergraduate researcher*” OR “student*”)) OR (AUTHKEY (“information retrieval*” OR “prompt engineering*” OR “ai literacy* OR "artificial intelligence*” OR “prompt training*” OR “formal training*” OR “chain of thought prompting*” OR “tree of thought prompting*” OR “prompt refinement*” OR “generative ai*” OR engineering technique*”) AND (“undergraduate*” OR “undergraduate researcher*” OR “student*”))

# data[].attributes.body
TITLE-ABS-KEY(("prompt engineering" OR "AI literacy") AND

("undergraduate student*" OR "undergraduate researcher*") AND ("information seeking" OR "search efficiency" OR "information quality") AND (training OR instruction))

# data[].attributes.body
TITLE-ABS-KEY(("prompt engineering" OR "prompt training" OR "AI literacy)

AND ("undergraduate student*")

AND ("information seeking" OR "search behavior*" OR "search efficien*" OR "information retrieval")

AND ("generative AI" OR ChatGPT OR "large language model*" OR LLM*))

# data[].attributes.body
TS= (("prompt engineering" OR "AI prompting" or "ChatGPT" or "Claude")) OR
AND ("formal training")
AND ("information-seeking behavior" OR "search behavior" OR "research behavior")
AND ("search efficiency")
AND ("college student*" OR "undergraduate researcher*"))

# data[].attributes.body
TS = (“prompt engineering" OR “prompt training” OR “AI prompting” OR “AI literacy" OR “chain-of-thought prompting“ OR “tree-of-thought prompting" ) AND TS = (“information quality” OR “search efficiency" ) AND TS = ( “generative AI” OR “large language model” OR “deep research”) AND TS = ("undergrad* research" OR "undergrad* studies")

# data[].attributes.body
TS = ((“prompt engineering” OR “AI prompting” OR LLM*) AND (training OR education OR workshop*) AND (“search efficiency” OR “information retrieval” OR “information-seeking behavior” OR “information quality”) AND (undergraduate* OR “college student*”))

# data[].attributes.body
TS=(("prompt engineering" OR "AI literacy") AND ("undergraduate student*" OR "college student*") AND ("information seeking" OR "search behavior*") AND ("generative AI" OR ChatGPT))

# data[].attributes.body
TS=(("prompt engineering" OR "AI literacy" OR ChatGPT) AND ("undergraduate student*" OR "undergraduate researcher*") AND ("information seeking" O "search efficiency" OR "information quality") AND (training OR instruction))

# data[].attributes.body
("prompt engineering" OR "AI prompting") AND ("information seeking behavior" OR "information seeking" OR "search behavior") AND ("undergraduate students" OR "undergraduate researcher" OR "student researcher") AND ("search efficiency" OR "search quality" OR "information quality")

# data[].attributes.body
ABSTRACT,TITLE("prompt engineering" OR "AI prompting") AND ("formal training")

AND ("information-seeking behavior" OR "research behavior")

AND ("search efficiency")

AND ("college student*" OR "undergraduate student*")

# data[].attributes.body
("prompt engineering" OR "AI literacy" OR ChatGPT))

AND ( "College Students" OR ("undergraduate student*")) AND

(("information seeking" OR "search efficiency" OR "information quality")) AND ((training OR instruction))

# data[].attributes.body
(("prompt engineering" OR "AI literacy") AND ("undergraduate student*" OR "higher education") AND ("information seeking" OR "search behavior*") AND ("generative AI" OR ChatGPT))

# data[].attributes.body
("prompt engineering" OR "AI prompting" OR "prompting techniques") AND ("information seeking" OR "information-seeking behavior" OR "search behavior" OR "information retrieval") AND ("search efficiency" OR "search performance" OR "retrieval quality" OR "search quality") AND ("undergraduate" OR "undergraduate students" OR "college students" OR "higher education") AND ("training" OR "instruction" OR "formal instruction" OR "information literacy")

# data[].attributes.body
prompt engineering

# data[].attributes.body
Chain-of-Thought Prompting

# data[].attributes.body
Generative AI

# data[].attributes.headline
temperature of responses, tokens (model cost amortization), 

# data[].attributes.subject
temperature of responses, tokens (model cost amortization), 

# data[].attributes.body
information retrieval

# data[].attributes.body
Tree of Thought Prompting

# data[].attributes.body
information seeking behaviors

# data[].attributes.body
information-seeking behaviors

# data[].attributes.body
undergraduate student researchers

# data[].attributes.body
Engineering techniques

# data[].attributes.body
machine learning

# data[].attributes.body
formal training, prompt engineering, information-seeking-behavior

# data[].attributes.body
LLM, Generative AI

# data[].attributes.body
Higher education research

# data[].attributes.body
AI search results

# data[].attributes.body
(“information retrieval*” OR “prompt engineering*” OR “ai literacy* OR "artificial intelligence*” OR “prompt training*” OR “formal training*” OR “chain of thought prompting*” OR “tree of thought prompting*” OR “prompt refinement*” OR “generative ai*” OR engineering technique*”) AND (“undergraduate*” OR “undergraduate researcher*” OR “student*”))

# data[].attributes.body
student researchers

# data[].attributes.body
non-students

# data[].attributes.body
2021 to present

# data[].attributes.body
use of formal training/instruction

# data[].attributes.body
no formal training in prompt engineering techniques

# data[].attributes.body
Use of only traditional databases

# data[].attributes.body
Information quality

# data[].attributes.body
Information seeking behavior

# data[].attributes.body
in traditional colleges

# data[].attributes.body
Studies in non-academic contexts

# data[].attributes.body
Quality of retrieved information

# data[].attributes.body
Faculty and Staff