The Impact of Generative Artificial Intelligence Dependency on Cognitive Function of University Students: A Cross-Sectional Study.
This observational cross-sectional study aims to investigate the relationship between dependence on generative artificial intelligence (AI) tools and cognitive functioning among university students.
調査の概要
詳細な説明
The increasing integration of generative artificial intelligence (GenAI) into higher education has transformed how university students access information, understand academic concepts, and complete learning activities. Although these technologies offer educational benefits, excessive dependence on AI-generated responses may be associated with cognitive offloading and reduced engagement in independent thinking and problem-solving.
This study aims to examine the association between generative AI dependency and cognitive functioning among university students, with particular attention to cognitive domains such as attention, memory, and executive functioning.
An observational cross-sectional design will be employed. Eligible university students aged 18-25 years will be invited to participate voluntarily through online announcements and electronic survey links. Informed consent will be obtained before data collection.
Participants will complete a structured online questionnaire collecting demographic and academic information, patterns of generative AI use, dependency-related responses, and measures of cognitive functioning.
The collected data will be analyzed using descriptive statistics, correlation analysis, and regression analysis to explore the relationship between AI dependency and cognitive functioning.
As this is a cross-sectional observational study, the results will identify possible associations but will not establish a causal relationship between generative AI dependency and changes in cognitive functioning.
The findings may contribute to understanding the educational implications of generative AI dependency and inform future research and teaching strategies promoting responsible AI use.
研究の種類
入学 (推定)
連絡先と場所
研究連絡先
- 名前：Sara Abdullah mohamed, PhD
- 電話番号：+20 11 51401438
- メール：sara.samahi@must.edu.eg
研究場所
-
-
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Giza、エジプト
- Faculty of Physical Therapy, Misr University for Science and Technology (MUST)
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コンタクト：
- Sara Abdullah mohamed, PhD
- 電話番号：+20 11 51401438
- メール：sara.samahi@must.edu.eg
-
-
参加基準
適格基準
就学可能な年齢
健康ボランティアの受け入れ
受講資格のある性別
サンプリング方法
調査対象母集団
The study population will include university students aged 18-25 years who use generative artificial intelligence (AI) tools for academic or daily activities. Eligible participants will be recruited from selected universities through electronic announcements, institutional emails, and online survey links. Participation will be voluntary, and informed consent will be obtained before completing the questionnaires assessing generative AI dependency and cognitive functioning.
説明
Inclusion Criteria:
- Enrolled undergraduate or graduate university students.
- Active users of digital devices and generative AI tools for academic or daily tasks.
- Ages between 18 and 25 years.
- Provided informed consent to participate in the study.
Exclusion Criteria:
- Diagnosed neurological or psychiatric disorders known to affect cognitive function.
- History of severe traumatic brain injury.
- Concurrent use of central nervous system-active medications that significantly alter cognitive performance.
- Incomplete questionnaire submissions.
研究計画
研究はどのように設計されていますか？
デザインの詳細
- 観測モデル：OTHER
- 時間の展望：CROSS_SECTIONAL
コホートと介入
グループ/コホート |
介入・治療 |
|---|---|
|
University Students
This cohort will include university students aged 18-25 years who use generative artificial intelligence (AI) tools. Participants will complete self-administered questionnaires assessing their level of generative AI dependency and cognitive functioning. Data will be collected at a single point in time to examine the association between these variables. No intervention will be administered. |
No Intervention: Observational Cohort |
この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Generative AI Dependency
時間枠：At enrollment (single assessment)
|
Measured via a validated Generative AI Dependency Scale or Questionnaire. |
At enrollment (single assessment)
|
二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Cognitive Function
時間枠：At enrollment (single assessment)
|
Assessed using standardized self-reported or validated neuropsychological instruments focusing on specific domains such as attention, memory, and executive function. |
At enrollment (single assessment)
|
協力者と研究者
捜査官
- 主任研究者：Sara Abdullah mohamed, PhD、Lecturer, MUST University
研究記録日
主要日程の研究
研究開始 (推定)
一次修了 (推定)
研究の完了 (推定)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
キーワード
その他の研究ID番号
- PT. BU. EC. 50
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
米国FDA規制機器製品の研究
この情報は、Web サイト clinicaltrials.gov から変更なしで直接取得したものです。研究の詳細を変更、削除、または更新するリクエストがある場合は、register@clinicaltrials.gov。 までご連絡ください。 clinicaltrials.gov に変更が加えられるとすぐに、ウェブサイトでも自動的に更新されます。