Shortcut to Knowledge or Shortcut to Thinking? Investigating AI-Induced Metacognitive Laziness in Future Doctors Article Swipe
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.21649/akemu.v31ispl2.6096
Background: The rapid expansion of artificial intelligence (AI) and machine learning has transformed industries, including education and healthcare. In medical education, AI is increasingly used for personalized learning and clinical decision-making. However, growing reliance on AI may contribute to metacognitive laziness, where students engage less in critical thinking and self-regulation. Objective: This study examines the relationship extent of AI reliance in medical students and its relationship with metacognitive laziness. Methods: The study involved medical and dental students, with data collected via a four-point Likert scale-based questionnaire. Content validity was ensured by expert ratings on relevance and clarity, and reliability was determined using Cronbach’s alpha. Descriptive statistics with median response category were used to describe students’ AI reliance, and Spearman’s rank correlation was used to analyze the relationship between AI reliance and metacognitive laziness, with a significance level set at p = 0.05. Results: The initial 47-item questionnaire was refined to 36 items, with an S-CVI/Ave of 0.88 and a CCA of 90%. Cronbach’s alpha was 0.936, indicating excellent reliability. The survey revealed that 74.4% of students relied on AI for learning, with 61.3% reporting decreased motivation for independent analysis and 62.4% expressing concerns about its impact on future patient care. Spearman’s rank correlation showed a moderate positive relationship (ρ = 0.621, p = 0.000). Conclusion: The increasing reliance on AI among medical students is associated with metacognitive laziness, emphasizing the need for careful AI integration to promote independent learning and critical thinking.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.21649/akemu.v31ispl2.6096
- OA Status
- diamond
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4413121419
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4413121419Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.21649/akemu.v31ispl2.6096Digital Object Identifier
- Title
-
Shortcut to Knowledge or Shortcut to Thinking? Investigating AI-Induced Metacognitive Laziness in Future DoctorsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-07-15Full publication date if available
- Authors
-
Mashaal Sabqat, Noorul Ain, Sana Iqbal, Rehan Ahmed KhanList of authors in order
- Landing page
-
https://doi.org/10.21649/akemu.v31ispl2.6096Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.21649/akemu.v31ispl2.6096Direct OA link when available
- Concepts
-
Laziness, Metacognition, Medicine, Psychiatry, CognitionTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4413121419 |
|---|---|
| doi | https://doi.org/10.21649/akemu.v31ispl2.6096 |
| ids.doi | https://doi.org/10.21649/akemu.v31ispl2.6096 |
| ids.openalex | https://openalex.org/W4413121419 |
| fwci | 2.28477614 |
| type | article |
| title | Shortcut to Knowledge or Shortcut to Thinking? Investigating AI-Induced Metacognitive Laziness in Future Doctors |
| biblio.issue | Spl2 |
| biblio.volume | 31 |
| biblio.last_page | 154 |
| biblio.first_page | 146 |
| topics[0].id | https://openalex.org/T11636 |
| topics[0].field.id | https://openalex.org/fields/27 |
| topics[0].field.display_name | Medicine |
| topics[0].score | 0.9765999913215637 |
| topics[0].domain.id | https://openalex.org/domains/4 |
| topics[0].domain.display_name | Health Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2718 |
| topics[0].subfield.display_name | Health Informatics |
| topics[0].display_name | Artificial Intelligence in Healthcare and Education |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C2776447739 |
| concepts[0].level | 2 |
| concepts[0].score | 0.9810685515403748 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q484 |
| concepts[0].display_name | Laziness |
| concepts[1].id | https://openalex.org/C118147538 |
| concepts[1].level | 3 |
| concepts[1].score | 0.8255814909934998 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q1126970 |
| concepts[1].display_name | Metacognition |
| concepts[2].id | https://openalex.org/C71924100 |
| concepts[2].level | 0 |
| concepts[2].score | 0.7182040810585022 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[2].display_name | Medicine |
| concepts[3].id | https://openalex.org/C118552586 |
| concepts[3].level | 1 |
| concepts[3].score | 0.1466425061225891 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q7867 |
| concepts[3].display_name | Psychiatry |
| concepts[4].id | https://openalex.org/C169900460 |
| concepts[4].level | 2 |
| concepts[4].score | 0.13245853781700134 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q2200417 |
| concepts[4].display_name | Cognition |
| keywords[0].id | https://openalex.org/keywords/laziness |
| keywords[0].score | 0.9810685515403748 |
| keywords[0].display_name | Laziness |
| keywords[1].id | https://openalex.org/keywords/metacognition |
| keywords[1].score | 0.8255814909934998 |
| keywords[1].display_name | Metacognition |
| keywords[2].id | https://openalex.org/keywords/medicine |
| keywords[2].score | 0.7182040810585022 |
| keywords[2].display_name | Medicine |
| keywords[3].id | https://openalex.org/keywords/psychiatry |
| keywords[3].score | 0.1466425061225891 |
| keywords[3].display_name | Psychiatry |
| keywords[4].id | https://openalex.org/keywords/cognition |
| keywords[4].score | 0.13245853781700134 |
| keywords[4].display_name | Cognition |
| language | en |
| locations[0].id | doi:10.21649/akemu.v31ispl2.6096 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2737983511 |
| locations[0].source.issn | 2079-0694, 2079-7192 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2079-0694 |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Annals of King Edward Medical University |
| locations[0].source.host_organization | https://openalex.org/P4310319300 |
| locations[0].source.host_organization_name | King Edward Medical University |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310319300 |
| locations[0].license | cc-by |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Annals of King Edward Medical University |
| locations[0].landing_page_url | https://doi.org/10.21649/akemu.v31ispl2.6096 |
| locations[1].id | pmh:oai:ojs2.localhost:article/6096 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306401876 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | The Diagnostic Pathology Journal (DiagnomX) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].source.host_organization_lineage | |
| locations[1].license | cc-by |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | Text |
| locations[1].license_id | https://openalex.org/licenses/cc-by |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | urn:ISSN:2016akemu.v31iSpl20 |
| locations[1].landing_page_url | https://annalskemu.org/journal/index.php/annals/article/view/6096 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5069231088 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Mashaal Sabqat |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Mashaal Sabqat |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5119273813 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Noorul Ain |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Noorul Ain |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5002651186 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-5049-5430 |
| authorships[2].author.display_name | Sana Iqbal |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Sana Iqbal |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5036808499 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-8045-1471 |
| authorships[3].author.display_name | Rehan Ahmed Khan |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | Rehan Ahmed Khan |
| authorships[3].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.21649/akemu.v31ispl2.6096 |
| open_access.oa_status | diamond |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Shortcut to Knowledge or Shortcut to Thinking? Investigating AI-Induced Metacognitive Laziness in Future Doctors |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11636 |
| primary_topic.field.id | https://openalex.org/fields/27 |
| primary_topic.field.display_name | Medicine |
| primary_topic.score | 0.9765999913215637 |
| primary_topic.domain.id | https://openalex.org/domains/4 |
| primary_topic.domain.display_name | Health Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2718 |
| primary_topic.subfield.display_name | Health Informatics |
| primary_topic.display_name | Artificial Intelligence in Healthcare and Education |
| related_works | https://openalex.org/W2899084033, https://openalex.org/W2748952813, https://openalex.org/W3031052312, https://openalex.org/W4389631184, https://openalex.org/W3004385792, https://openalex.org/W4234237255, https://openalex.org/W3151953821, https://openalex.org/W2375733006, https://openalex.org/W3110783916, https://openalex.org/W3164750567 |
| cited_by_count | 1 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| locations_count | 2 |
| best_oa_location.id | doi:10.21649/akemu.v31ispl2.6096 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2737983511 |
| best_oa_location.source.issn | 2079-0694, 2079-7192 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2079-0694 |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Annals of King Edward Medical University |
| best_oa_location.source.host_organization | https://openalex.org/P4310319300 |
| best_oa_location.source.host_organization_name | King Edward Medical University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310319300 |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Annals of King Edward Medical University |
| best_oa_location.landing_page_url | https://doi.org/10.21649/akemu.v31ispl2.6096 |
| primary_location.id | doi:10.21649/akemu.v31ispl2.6096 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2737983511 |
| primary_location.source.issn | 2079-0694, 2079-7192 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2079-0694 |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Annals of King Edward Medical University |
| primary_location.source.host_organization | https://openalex.org/P4310319300 |
| primary_location.source.host_organization_name | King Edward Medical University |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310319300 |
| primary_location.license | cc-by |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Annals of King Edward Medical University |
| primary_location.landing_page_url | https://doi.org/10.21649/akemu.v31ispl2.6096 |
| publication_date | 2025-07-15 |
| publication_year | 2025 |
| referenced_works_count | 0 |
| abstract_inverted_index.= | 140, 209, 212 |
| abstract_inverted_index.a | 81, 134, 158, 204 |
| abstract_inverted_index.p | 139, 211 |
| abstract_inverted_index.36 | 150 |
| abstract_inverted_index.AI | 21, 35, 58, 115, 128, 178, 219, 233 |
| abstract_inverted_index.In | 18 |
| abstract_inverted_index.an | 153 |
| abstract_inverted_index.at | 138 |
| abstract_inverted_index.by | 90 |
| abstract_inverted_index.in | 45, 60 |
| abstract_inverted_index.is | 22, 223 |
| abstract_inverted_index.of | 4, 57, 155, 160, 174 |
| abstract_inverted_index.on | 34, 93, 177, 196, 218 |
| abstract_inverted_index.to | 38, 112, 123, 149, 235 |
| abstract_inverted_index.(ρ | 208 |
| abstract_inverted_index.CCA | 159 |
| abstract_inverted_index.The | 1, 70, 143, 169, 215 |
| abstract_inverted_index.and | 8, 16, 28, 48, 63, 74, 95, 97, 117, 130, 157, 189, 239 |
| abstract_inverted_index.for | 25, 179, 186, 231 |
| abstract_inverted_index.has | 11 |
| abstract_inverted_index.its | 64, 194 |
| abstract_inverted_index.may | 36 |
| abstract_inverted_index.set | 137 |
| abstract_inverted_index.the | 54, 125, 229 |
| abstract_inverted_index.via | 80 |
| abstract_inverted_index.was | 88, 99, 121, 147, 164 |
| abstract_inverted_index.(AI) | 7 |
| abstract_inverted_index.0.88 | 156 |
| abstract_inverted_index.90%. | 161 |
| abstract_inverted_index.This | 51 |
| abstract_inverted_index.data | 78 |
| abstract_inverted_index.less | 44 |
| abstract_inverted_index.need | 230 |
| abstract_inverted_index.rank | 119, 201 |
| abstract_inverted_index.that | 172 |
| abstract_inverted_index.used | 24, 111, 122 |
| abstract_inverted_index.were | 110 |
| abstract_inverted_index.with | 66, 77, 106, 133, 152, 181, 225 |
| abstract_inverted_index.0.05. | 141 |
| abstract_inverted_index.61.3% | 182 |
| abstract_inverted_index.62.4% | 190 |
| abstract_inverted_index.74.4% | 173 |
| abstract_inverted_index.about | 193 |
| abstract_inverted_index.alpha | 163 |
| abstract_inverted_index.among | 220 |
| abstract_inverted_index.care. | 199 |
| abstract_inverted_index.level | 136 |
| abstract_inverted_index.rapid | 2 |
| abstract_inverted_index.study | 52, 71 |
| abstract_inverted_index.using | 101 |
| abstract_inverted_index.where | 41 |
| abstract_inverted_index.0.621, | 210 |
| abstract_inverted_index.0.936, | 165 |
| abstract_inverted_index.Likert | 83 |
| abstract_inverted_index.alpha. | 103 |
| abstract_inverted_index.dental | 75 |
| abstract_inverted_index.engage | 43 |
| abstract_inverted_index.expert | 91 |
| abstract_inverted_index.extent | 56 |
| abstract_inverted_index.future | 197 |
| abstract_inverted_index.impact | 195 |
| abstract_inverted_index.items, | 151 |
| abstract_inverted_index.median | 107 |
| abstract_inverted_index.relied | 176 |
| abstract_inverted_index.showed | 203 |
| abstract_inverted_index.survey | 170 |
| abstract_inverted_index.0.000). | 213 |
| abstract_inverted_index.47-item | 145 |
| abstract_inverted_index.Content | 86 |
| abstract_inverted_index.analyze | 124 |
| abstract_inverted_index.between | 127 |
| abstract_inverted_index.careful | 232 |
| abstract_inverted_index.ensured | 89 |
| abstract_inverted_index.growing | 32 |
| abstract_inverted_index.initial | 144 |
| abstract_inverted_index.machine | 9 |
| abstract_inverted_index.medical | 19, 61, 73, 221 |
| abstract_inverted_index.patient | 198 |
| abstract_inverted_index.promote | 236 |
| abstract_inverted_index.ratings | 92 |
| abstract_inverted_index.refined | 148 |
| abstract_inverted_index.However, | 31 |
| abstract_inverted_index.Methods: | 69 |
| abstract_inverted_index.Results: | 142 |
| abstract_inverted_index.analysis | 188 |
| abstract_inverted_index.category | 109 |
| abstract_inverted_index.clarity, | 96 |
| abstract_inverted_index.clinical | 29 |
| abstract_inverted_index.concerns | 192 |
| abstract_inverted_index.critical | 46, 240 |
| abstract_inverted_index.describe | 113 |
| abstract_inverted_index.examines | 53 |
| abstract_inverted_index.involved | 72 |
| abstract_inverted_index.learning | 10, 27, 238 |
| abstract_inverted_index.moderate | 205 |
| abstract_inverted_index.positive | 206 |
| abstract_inverted_index.reliance | 33, 59, 129, 217 |
| abstract_inverted_index.response | 108 |
| abstract_inverted_index.revealed | 171 |
| abstract_inverted_index.students | 42, 62, 175, 222 |
| abstract_inverted_index.thinking | 47 |
| abstract_inverted_index.validity | 87 |
| abstract_inverted_index.S-CVI/Ave | 154 |
| abstract_inverted_index.collected | 79 |
| abstract_inverted_index.decreased | 184 |
| abstract_inverted_index.education | 15 |
| abstract_inverted_index.excellent | 167 |
| abstract_inverted_index.expansion | 3 |
| abstract_inverted_index.including | 14 |
| abstract_inverted_index.laziness, | 40, 132, 227 |
| abstract_inverted_index.laziness. | 68 |
| abstract_inverted_index.learning, | 180 |
| abstract_inverted_index.relevance | 94 |
| abstract_inverted_index.reliance, | 116 |
| abstract_inverted_index.reporting | 183 |
| abstract_inverted_index.students, | 76 |
| abstract_inverted_index.thinking. | 241 |
| abstract_inverted_index.Objective: | 50 |
| abstract_inverted_index.artificial | 5 |
| abstract_inverted_index.associated | 224 |
| abstract_inverted_index.contribute | 37 |
| abstract_inverted_index.determined | 100 |
| abstract_inverted_index.education, | 20 |
| abstract_inverted_index.expressing | 191 |
| abstract_inverted_index.four-point | 82 |
| abstract_inverted_index.increasing | 216 |
| abstract_inverted_index.indicating | 166 |
| abstract_inverted_index.motivation | 185 |
| abstract_inverted_index.statistics | 105 |
| abstract_inverted_index.Background: | 0 |
| abstract_inverted_index.Conclusion: | 214 |
| abstract_inverted_index.Descriptive | 104 |
| abstract_inverted_index.correlation | 120, 202 |
| abstract_inverted_index.emphasizing | 228 |
| abstract_inverted_index.healthcare. | 17 |
| abstract_inverted_index.independent | 187, 237 |
| abstract_inverted_index.industries, | 13 |
| abstract_inverted_index.integration | 234 |
| abstract_inverted_index.reliability | 98 |
| abstract_inverted_index.scale-based | 84 |
| abstract_inverted_index.students’ | 114 |
| abstract_inverted_index.transformed | 12 |
| abstract_inverted_index.Cronbach’s | 102, 162 |
| abstract_inverted_index.Spearman’s | 118, 200 |
| abstract_inverted_index.increasingly | 23 |
| abstract_inverted_index.intelligence | 6 |
| abstract_inverted_index.personalized | 26 |
| abstract_inverted_index.relationship | 55, 65, 126, 207 |
| abstract_inverted_index.reliability. | 168 |
| abstract_inverted_index.significance | 135 |
| abstract_inverted_index.metacognitive | 39, 67, 131, 226 |
| abstract_inverted_index.questionnaire | 146 |
| abstract_inverted_index.questionnaire. | 85 |
| abstract_inverted_index.decision-making. | 30 |
| abstract_inverted_index.self-regulation. | 49 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.84248386 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |