Oalib Open Access Library Journal 2333-9705 2333-9721 Scientific Research Publishing 10.4236/oalib.1113885 Oalib-144785 Articles Biomedical Life Sciences, Business Economics, Chemistry Materials Science, Computer Science Communications, Earth Environmental Sciences, Engineering, Medicine Healthcare, Physics Mathematics, Social Sciences Humanities Exploring the Link between ChatGPT Utilization, Academic Resilience, and Academic Achievement of STEM Students Neil Emilson N. Santiago Maria Andrea G. Bucaloy John Christian M. Delos Reyes Maricris A. Vallente Christopher R. Vergara aCollege of Education, Nueva Ecija University of Science and Technology, Cabanatuan, Philippines 01 08 2025 12 08 1 26 30, June 2025 11, June 2025 11, August 2025 © Copyright 2014 by authors and Scientific Research Publishing Inc. 2014 This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Generative artificial intelligence (AI) has gained considerable attention in recent educational discourse. Still, empirical evidence on its pedagogical value, particularly in science domains such as biology, remains limited and inconclusive. The study surveyed 230 Filipino senior-high Science, Technology, Engineering, and Mathematics (STEM) learners to determine how knowledge, attitudes and practices toward ChatGPT relate to biology grades and whether academic resilience mediates this link. Using validated KAP-CQ and ARS-30 questionnaires, the authors applied descriptive statistics, Pearson correlations, multiple regression and Hayes’ mediation procedure. Results revealed that among the dimensions of ChatGPT utilization, only students’ knowledge of the educational use of ChatGPT demonstrated a significant positive correlation with biology achievement and emerged as a significant predictor of performance. Moreover, this dimension also showed a positive correlation with perseverance, a key subcomponent of academic resilience. Additionally, students’ attitudes toward ChatGPT exhibited significant associations with both perseverance and reflective, adaptive help-seeking behaviors. However, academic resilience did not mediate the relationship between the use of ChatGPT and academic performance. These findings suggest that fostering informed and strategic use of AI tools may enhance learning outcomes in STEM education. The study highlights the importance of structured student training on AI’s educational applications, emphasizing not only functional knowledge but also the development of responsible and resilient learning behaviors.Subject AreasEducation, Educational Psychology, Educational Technology ChatGPT Utilization Academic Resilience Academic Achievement STEM 1. 引言近年来，随着多媒体技术和经济多元全球化的不断发展，跨界思维不断冲击着传统的品牌联合，电商、餐饮、服装等行业相继掀起跨界联合风潮，营销学之父菲利普·科特勒曾经说过：除了主流品牌和小众品牌以外，混合品牌也将在未来占据一席之地，其中这个混合品牌与后面的“跨界品牌联合”在某种程度上是一样的，跨界品牌联合是指处于不同行业边界的品牌跨边界进行合作共同推出新产品 [1] 。在跨界联合的实践过程中有的品牌跨界备受关注，溢出效应明显，例如Rio华为手机结合保时捷设计出的超级旗舰MateRS设计好评如潮，大白兔品牌奶糖与加美净这类日化品牌推出的奶糖味的唇膏，上架即一扫而光，然而有的跨界联合却反响平平，甚至出现负面溢出效果，例如喜茶与杜蕾斯的联合产品没有得到消费者的积极评价，甚至使消费者产生反感情绪。之前关于品牌联合效果影响因素的分析上主要体现在联合匹配性、在产品关系和逻辑上的契合度，以及品牌要素互补性方面，但是在研究跨界联合时没有考虑到跨界品牌双方本身就具有较大的差异性，所以在一定程度上对跨界联合的成败现象并不能完全解释。因此，本文聚焦品牌跨界联合情景下，根据形式与功能的整合程度将品牌跨界联合的整合度分为高、低两种，基于SOR模型 [2] ，进而分析品牌跨界联合时的整合度高低对消费者品牌联合评价的影响机制，并且在这个基础上研究消费者感知价值在品牌跨界联合时的整合度对消费者品牌联合评价的中介作用。 2. 文献回顾及研究假设(一) 品牌跨界联合整合度与消费者品牌联合评价相关研究有关品牌跨界联合的概念大多围绕跨界营销进行，在市场营销中有共生营销的概念，它是指一种合作联盟关系，合作双方及多方为实现资源共享，提升竞争能力而形成的一种长期或者短期联盟合作关系，而品牌跨界联合则是指两个异质行业、互相独立但拥有平等商业地位的品牌通过活化老品牌，共享互补资源，降低成本等方式以推出新产品，从而实现销售额的增加 [3] 。两者具有一定的相似性，因此根据前人的论述及本文的研究内容将品牌跨界联合大致定义为品牌联合的特殊形式，是指同一个新的产品中存有两个来自不同且没有竞争关系行业的品牌。由于合作品牌双方的合作程度对消费者的品牌评价会产生相应的影响，Newmeyer等(2018) [4] 根据联合产品在形式和功能上的结合程度提出了六种整合度不同的品牌联合形式，从低到高依次为同地品牌联合、共同促销、捆绑联合、成分联合、要素联合、共同研发联合，本文根据形式和功能的结合程度，将共同研发联合和元素联合划分为高度整合，成分联合和捆绑联合划分为中度整合，共同促销和同地品牌联合划分为低度整合。一个品牌产品所带来的功能或者形式较为单一，不能满足消费者日益多元的功能需求和价值需求，如果将两个异质性产品进行跨界联合，不仅能够带来冲击固有认知的创新感，还有益于提升消费者的忠诚度，但是差异过大的品牌联合可能会产生负面溢出效应 [5] 。所以大多学者聚焦于品牌跨界联合前的联合匹配性和契合度的研究，忽视了品牌跨界联合过程中的整合程度，而消费者对跨界品牌联合的评价在一定层面上反映出跨界联合双方合作的效果，较高的评价不仅有助于维持对品牌资产较好品牌的忠诚度，还有利于提升品牌资产较弱一方的品牌形象(Lin, 2013)，在跨界品牌联合中合作双方的交融程度越深，即产品整合度越高，越有益于消费者体验到品牌双方各自的优势，感受到跨界联合产品所带来的新奇与价值感，从而促进消费者对跨界品牌联合作出积极评价。综上所述，本文提出假设1：H1：在品牌跨界联合时，产品整合度对品牌联合评价有正向影响。(二) 在品牌跨界联合时，感知价值在产品联合整合度对品牌联合评价中的中介作用消费者感知价值这一概念是基于现代营销中的消费者价值理论，该理论认为营销其实是交换价值与感知价值的过程，消费者在得到产品后会对其付出成本与感知价值效用进行比较，从而给出整体评价 [6] 。消费者感知价值时往往有三个特征，对产品价值会根据自身主观性进行感知，并且倾向于在比较中感知价值，其感知的价值还具有阶梯性 [7] 。因此，范秀成等(2003) [8] 将消费者感知价值概述为消费者对企业提供的产品和服务价值的主观评价，当消费者感知到价值时会对品牌联合产生积极评价，而产品整合度越高，即跨界联合产品无论是形式还是功能方面都高度融合，没有令消费者产生突兀感，能够驱动消费者产生价值感知，将异质的产品进行创新融合，起初的不匹配性能够打破了对原有品牌的刻板印象，再通过后面的高度整合能够使消费者产生创新感知的同时降低跨界创新产品的不确定性，感受到品牌联合带来的综合价值，而消费者的感知价值会影响消费者对品牌的选择，进而促进消费者对品牌联合作出正向评价 [9] 。因此，本文假设在品牌跨界联合过程中，合作双方后期在形式和功能上的产品整合度将影响消费者感知价值，又因为高整合度与品牌联合评价具有正向影响，推测消费者感知价值也将正向影响品牌联合评价。综上所述，本文提出假设2：H2：在品牌跨界联合时，消费者感知价值在产品整合度对消费者品牌联合评价的影响中起到中介作用。基于此，本文以SOR模型为研究框架，将品牌框架联合时的产品整合度作为刺激源，消费者从中获得的价值感知作为个体心理呈现，消费者对品牌联合的评价作为消费者者反应，构建在品牌跨界联合中产品整合程度对品牌联合评价的影响模型，模型如 图1 所示。 <xref ref-type="bibr" rid="oalib.144785-"></xref>Figure 1. Research model图1. 研究模型 图1. 研究模型 3. 实证设计与研究发现1) 研究设计与数据收集这部分由前测和正式实验组成，前测主要是通过了解市场上影响较广的跨界联合产品，并由此确定实验对象，正式实验根据产品组合利用单因素两水平，即产品整合程度高低的组间设计，检验品牌跨界联合时产品整合程度对品牌联合评价的主要影响以及消费者价值感知对其中的中介效应。① 前测。通过网络咨询了解与品牌跨界词条有关的内容，其中包含了有关跨界产品组合功能与形式的324条记录。选择了6组市面上真实的跨界组合案例，分别为蔻驰皮革的贝克家具、加入当尼柔顺剂的汰渍洗衣液、安装劳斯莱斯发动机的空客机、戴尔电脑与佳能打印机、配有迪士尼玩具的儿童餐、出售赛百味三明治的沃尔玛。通过变动产品整合度的操纵方法，让受访者填写整合度的7级量表 [4] ，对这些组合的产品整合度进行打分。此次前测收回有效问卷78份，并通过统计数据分析得出，蔻驰皮革的贝克家具这组共同研发组合的整合度评分均值为M 整合度 = 5.26，出售赛百味三明治的沃尔玛这组同地品牌联合销售的整合度评分均值为M 整合度 = 4.14，两者之间的差异很明显，将蔻驰皮革的贝克家具作为高整合度组合，而将出售赛百味三明治的沃尔玛作为低整合度组合，并将两组组合作为实验的刺激源。② 正式实验。该实验采用单因素两水平的设计，包括了102名消费者，其中人员年龄集中于26~35岁，男性占比42.15%，女性占比57.85%，教育程度占比主要是本科学历，将被试进行随机等量分配，其中高低整合度组各自均为61人。让产品高整合度组的被试浏览蔻驰皮革的贝克家具在功能和形式上的整合材料信息，同时让产品低整合度组的被试浏览沃尔玛出售赛百味三明治的销售整合信息，两组被试在看到品牌跨界联合刺激材料后如实填写产品感知价值量表以及品牌联合评价量表，具体量表题项如 表1 所示。 <xref ref-type="bibr" rid="oalib.144785-"></xref>Table 1. Measurement scaleTable 1. Measurement scale 表1. 测量量表

测量维度

测量题项参考来源

消费者感知价值

讨论/拥有/分享这项联名让我很开心

李慧，周雨(2021)

讨论/拥有/分享这项联名让我给他人留下了好印象

这项联名让我获得了自我满足

Sweeney and Soutar (2001)

该联名是我喜欢的

讨论/拥有/分享这项联名让我结识了很多朋友

品牌联合评价

我认为该产品很吸引人

Shih等(2013)

我非常喜欢该联合产品

该联合产品表达了我的个性
2) 数据分析① 问卷的信效度检验。利用SPSS 24.0对实验中的数据进行信度与效度的检验，其中产品感知价值量表以及品牌联合评价量表的Cronbach’ α系数分别为0.891、0.912，两者均在0.8以上，说明问卷信度较好。同时，通过验证性因子分析得出组合的CR和AVE值，从中发现组合效度AR值大于0.7，说明所选题项的一致性好，AVE值也达到了推荐的标准，所以该变量具有较好的效度。②主效应检验。在品牌跨界联合中，通过独立样本T检验验证产品整合度对消费者品牌联合评价有显著影响，即主效应检验。如 表2 所示，产品整合度不同，消费者对品牌跨界联合评价也显著不同，在产品整合度较高的跨界联合中，消费者对品牌联合评价(M = 2.811)显著高于产品整合度低的跨界联合产品(M = 1.649)，因此本文的假设1得到验证，即在品牌跨界联合时，产品整合度对品牌联合评价有正向影响。 <xref ref-type="bibr" rid="oalib.144785-"></xref>Table 2. Comparison of consumers’ evaluation of co-brand under different product integration degreesTable 2. Comparison of consumers’ evaluation of co-brand under different product integration degrees 表2. 不同产品整合度下消费者对品牌联合评价的差异比较

整合度分组

个案数

平均值

标准差

T值

品牌联合评价

高整合度

61

2.811

0.678

−5.650***

低整合度

61

1.649

0.718
③ 中介效应检验。本文以跨界产品整合度为自变量、消费者感知价值为中介变量、品牌联合评价为因变量，运用PROCESS程序中的model 4，通过Bootstrap方法对感知价值的中介效应进行检验，其中控制性别、年龄等人口特征变量。结果显示，产品整合程度对品牌联合评价的总效应为0.942，95%置信区间为(0.642, 1.193)，直接效应为0.401，95%置信区间为(0.076, 0.723)，均不包括0，产品整合程度对消费者感知价值具有显著的正向影响[B = 1.231, 95%置信区间为(0.844, 1.713), SE = 0.231, t = 5.895, p < 0.01]，消费者感知价值对品牌联合评价具有显著正向影响[B = 0.449, 95%置信区间为(0.289, 0.589), SE = 0.071, t = 6.334, p < 0.01]，从产品整合度到感知价值，再到品牌联合评价，其中的间接效应为0.673，95%的置信区间(0.302, 0.937)，不含0，由此得以验证感知价值在产品整合程度与品牌联合评价关系里起到中介作用。 4. 结论与启示本文通过实证分析研究了处于品牌跨界联合中，产品整合度对品牌联合评价的影响关系，主要得到两个结论：首先，在品牌跨界联合时，相比于产品整合度较低的跨界组合，产品整合度高的跨界组合更能够带来积极的品牌联合评价，即产品整合度对品牌联合评价有正向影响；其次，消费者感知价值在跨界产品整合度对品牌联合评价的影响中起到中介作用。通过实证研究，发现产品整合度越高，越有利于消费者感知价值，同时当消费者感知价值以后会对品牌联合作出积极评价，即消费者感知价值在跨界产品整合度和品牌联合评价中起到中介作用。而SOR理论正是关于刺激对个体心理产生影响，从而产生反应的研究模型，因此本文基于SOR理论，在品牌跨界联合时，产品整合度高这一刺激源使得消费者根据偏好流畅性的心理会降低对跨界创新产品的不确定性，从而增强消费者对该类商品的接受度，并从中感知到联合的综合价值。当消费者感受到情绪价值或者社会价值时会产生积极反应，即较高的品牌联合评价，这不仅维持了消费者对原有品牌产品的忠诚度，又在一定程度上提升了品牌资产，为企业有针对性地进行品牌跨界联合提供了感知价值角度的理论支持。本文的研究为企业进行跨界创新实践活动提供了相应指导。首先，尽管市场上出现的跨界创新现象层出不穷，与不同的品牌进行跨界创新能够在短期内快速吸引消费者，并从长期唤起品牌活力，提升品牌创新能力，但是在这个过程中企业应该结合自身的发展情况和战略模式进行调整，不要跟风进行盲目跨界。合适的跨界能够带来正面效应，但是如果缺少跨界的前提情景和适宜时机，跨界将给企业的发展带来无论是品牌形象还是消费者受众都产生消极影响。其次，在品牌跨界联合时，除了考虑前期匹配性，还需要进行整合度的规划。许多企业在进行品牌联合时往往考虑合作双方固有的形象或者市场是否匹配，匹配性较大可以提升消费者的可接受度，但是也可能固化消费者认知。对于需要进行品牌跨界转型的企业来说，同质品牌联合对于公司的发展战略来说意义不大，如果品牌联合异质性较大，品牌联合发行起初可能会吸引眼球，赚取热度，收获许多受众；对于品牌资产不对等的双方来说，影响也不尽相同，但后期消费者感知的功能和形式方面的异质性过于突出，可能会引起消费者的排斥心理，进而降低消费者评价。企业可以通过提升联合产品在功能和形式方面的交融整合度，产品整合度高时消费者更加容易理解品牌联合的意义和价值，也能够避免品牌联合带来的不适感，降低消费者对冲击固有认知的排斥，进而更加理解品牌融合的真正目的以及给自身带来的价值，有利于提升消费者对品牌联合的认同感，对品牌联合做出积极评价，将不匹配产品转换为一次具有创新意义的匹配产品。最后，如果将跨界产品匹配性作为消费者是否接受的前提条件，那么整合度的提升将有益于消费者从中感受到该跨界联合所带来的综合价值。好的品牌联合除了考虑前期双方的联合匹配度，也要形成良好的产品整合度，如果前期的匹配度不能达到预期，那么可以通过后期从产品和功能方面对匹配联合整合度进行调整，从而激发消费者的购买意愿以及对该品牌联合的积极评价。所以企业在实践中要注意消费者感知价值在产品整合度对品牌联合评价中的中介作用，通过良好的整合促使消费者感知产品价值，进而提升品牌联合评价。 References Rudolph, J., Tan, S. and Tan, S. (2023) ChatGPT: Bullshit Spewer or the End of Traditional Assessments in Higher education? Journal of Applied Learning & Teaching, 6, 342-363. >https://doi.org/10.37074/jalt.2023.6.1.9 Sullivan, M., Kelly, A. and McLaughlan, P. (2023) ChatGPT in Higher Education: Considerations for Academic Integrity and Student Learning. Journal of Applied Learning & Teaching, 6, 1-10. >https://doi.org/10.37074/jalt.2023.6.1.17 Al-Afnan, M.A., Dishari, S., Jovic, M. and Lomidze, K. (2023) ChatGPT as an Educational Tool: Opportunities, Challenges, and Recommendations for Communication, Business Writing, and Composition Courses. Journal of Artificial Intelligence and Technology, 3, 60-68. >https://doi.org/10.37965/jait.2023.0184 Roumeliotis, K.I. and Tselikas, N.D. (2023) ChatGPT and Open-AI Models: A Preliminary Review. Future Internet, 15, Article 192. >https://doi.org/10.3390/fi15060192 Chukwuere, J.E. (2023) ChatGPT: The Game Changer for Higher Education Institutions. Jozac Academic Voice, 3, 22-27. Cheung, B.H.H., Lau, G.K.K., Wong, G.T.C., Lee, E.Y.P., Kulkarni, D., Seow, C.S., et al. (2025) Correction: ChatGPT versus Human in Generating Medical Graduate Exam Multiple Choice Questions—A Multinational Prospective Study (Hong Kong S.A.R., Singapore, Ireland, and the United Kingdom). PLOS One, 20, e0327290. >https://doi.org/10.1371/journal.pone.0327290 Ding, L., Li, T., Jiang, S. and Gapud, A. (2023) Students’ Perceptions of Using ChatGPT in a Physics Class as a Virtual Tutor. International Journal of Educational Technology in Higher Education, 20, Article No. 63. >https://doi.org/10.1186/s41239-023-00434-1 Firat, M. (2023) What ChatGPT Means for Universities: Perceptions of Scholars and Students. Journal of Applied Learning and Teaching, 6, 57-63. >https://doi.org/10.37074/jalt.2023.6.1.22 Zhai, X. (2022) ChatGPT User Experience: Implications for Education. SSRN Electronic Journal. >https://doi.org/10.2139/ssrn.4312418 Firaina, R. and Sulisworo, D. (2023) Exploring the Usage of ChatGPT in Higher Education: Frequency and Impact on Productivity. Buletin Edukasi Indonesia, 2, 39-46. >https://doi.org/10.56741/bei.v2i01.310 Farhi, F., Jeljeli, R., Aburezeq, I., Dweikat, F.F., Al-shami, S.A. and Slamene, R. (2023) Analyzing the Students’ Views, Concerns, and Perceived Ethics about ChatGPT Usage. Computers and Education: Artificial Intelligence, 5, Article ID: 100180. >https://doi.org/10.1016/j.caeai.2023.100180 Adeshola, I. and Adepoju, A.P. (2023) The Opportunities and Challenges of ChatGPT in Education. Interactive Learning Environments, 32, 6159-6172. >https://doi.org/10.1080/10494820.2023.2253858 Vargas-Murillo, A.R., Pari-Bedoya, I.N.M.D.L.A. and Guevara-Soto, F.D.J. (2023) Challenges and Opportunities of AI-Assisted Learning: A Systematic Literature Review on the Impact of ChatGPT Usage in Higher Education. International Journal of Learning, Teaching and Educational Research, 22, 122-135. >https://doi.org/10.26803/ijlter.22.7.7 Cassidy, S. (2016) The Academic Resilience Scale (ARS-30): A New Multidimensional Construct Measure. Frontiers in Psychology, 7, Article 1787. >https://doi.org/10.3389/fpsyg.2016.01787 Ye, W., Strietholt, R. and Blömeke, S. (2021) Academic Resilience: Underlying Norms and Validity of Definitions. Educational Assessment, Evaluation and Accountability, 33, 169-202. >https://doi.org/10.1007/s11092-020-09351-7 Kalaivani, D. (2021) Academic Resilience among Students: A Review of Literature. International Journal of Research and Review, 8, 360-369. >https://doi.org/10.52403/ijrr.20210646 Romano, L., Angelini, G., Consiglio, P. and Fiorilli, C. (2021) Academic Resilience and Engagement in High School Students: The Mediating Role of Perceived Teacher Emotional Support. European Journal of Investigation in Health, Psychology and Education, 11, 334-344. >https://doi.org/10.3390/ejihpe11020025 García-Crespo, F.J., Fernández-Alonso, R. and Muñiz, J. (2021) Academic Resilience in European Countries: The Role of Teachers, Families, and Student Profiles. PLOS ONE, 16, e0253409. >https://doi.org/10.1371/journal.pone.0253409 Vergara, C.R. (2024) Examining the Relationship of Mathematics Self-Concept, Academic Self-Regulation, and Academic Achievement of Pre-Service Mathematics Teachers. OALib, 11, 1-18. >https://doi.org/10.4236/oalib.1111816 Choo, O.Z.H. and Prihadi, K.D. (2019) Academic Resilience as Mediator of Multidimensional Perfectionism and Academic Performance among Gen-Z Undergraduate Students. International Journal of Evaluation and Research in Education (IJERE), 8, 637-646. >https://doi.org/10.11591/ijere.v8i4.20340 Fang, G., Keung Chan, P.W. and Kalogeropoulos, P. (2020) Social Support and Academic Achievement of Chinese Low-Income Children: A Mediation Effect of Academic Resilience. International Journal of Psychological Research, 13, 19-28. >https://doi.org/10.21500/20112084.4480 Fullerton, D.J., Zhang, L.M. and Kleitman, S. (2021) An Integrative Process Model of Resilience in an Academic Context: Resilience Resources, Coping Strategies, and Positive Adaptation. PLOS ONE, 16, e0246000. >https://doi.org/10.1371/journal.pone.0246000 Shahidi Delshad, E., Nobahar, M., Raiesdana, N., Yarahmadi, S. and Saberian, M. (2023) Academic Resilience, Moral Perfectionism, and Self-Compassion among Undergraduate Nursing Students: A Cross-Sectional, Multi-Center Study. Journal of Professional Nursing, 46, 39-44. >https://doi.org/10.1016/j.profnurs.2023.02.006 Rudd, G., Meissel, K. and Meyer, F. (2022) Investigating the Measurement of Academic Resilience in Aotearoa New Zealand Using International Large-Scale Assessment Data. Educational Assessment, Evaluation and Accountability, 35, 169-200. >https://doi.org/10.1007/s11092-022-09384-0 Nguyen, X.H., Nguyen, H.A., Cao, L. and Hana, T. (2023) Potential of ChatGPT in Biology Teaching and Learning at the Vietnamese High School. Authorea. >https://doi.org/10.22541/au.169029376.68639796/v1 Koć-Januchta, M.M., Schönborn, K.J., Tibell, L.A.E., Chaudhri, V.K. and Heller, H.C. (2020) Engaging with Biology by Asking Questions: Investigating Students’ Interaction and Learning with an Artificial Intelligence-Enriched Textbook. Journal of Educational Computing Research, 58, 1190-1224. >https://doi.org/10.1177/0735633120921581 Owusu, K.A., Monney, K.A., Appiah, J.Y. and Wilmot, E.M. (2010) Effects of Computer-Assisted Instruction on Performance of Senior High School Biology Students in Ghana. Computers & Education, 55, 904-910. >https://doi.org/10.1016/j.compedu.2010.04.001 Forman, N., Udvaros, J. and Avornicului, M.S. (2023) ChatGPT: A New Study Tool Shaping the Future for High School Students. International Journal of Advanced Natural Sciences and Engineering Researches, 7, 95-102. >https://doi.org/10.59287/ijanser.562 Alneyadi, S. and Wardat, Y. (2023) ChatGPT: Revolutionizing Student Achievement in the Electronic Magnetism Unit for Eleventh-Grade Students in Emirates Schools. Contemporary Educational Technology, 15, ep448. >https://doi.org/10.30935/cedtech/13417 Swargiary, K. (2023) The Impact of ChatGPT on Student Learning Behavior: An Experimental Research Study. SSRN Electronic Journal. >https://doi.org/10.2139/ssrn.4611213 Ali, R.S., Syarifah, P.N., Rohmah, Y. and Perdhana, M.S. (2023) Understanding the Academic Resilience of Students in Managing Coursework Responsibilities and the Rationale behind the Usage of ChatGPT. Proceedings of International Conference on Psychological Studies (ICPsyche), 4, 30-42. >https://doi.org/10.58959/icpsyche.v4i1.21 Kelly, D. and Donaldson, D.I. (2016) Annual Conference 2015 Paper Investigating the Complexities of Academic Success: Personality Constrains the Effects of Metacognition. Psychology of Education Review, 40, 17-23. >https://doi.org/10.53841/bpsper.2016.40.2.17 Steinmayr, R., Meißner, A., Weidinger, A.F. and Wirthwein, L. (2014) Academic Achievement. Education, 1, 1-2. >https://doi.org/10.1093/obo/9780199756810-0108 Gilar-Corbi, R., Veas, A., Miñano, P. and Castejón, J. (2019) Differences in Personal, Familial, Social, and School Factors between Underachieving and Non-Underachieving Gifted Secondary Students. Frontiers in Psychology, 10, Article 2367. >https://doi.org/10.3389/fpsyg.2019.02367 Araújo, A.M. (2017) Sucesso no Ensino Superior: Uma revisão e conceptualização [Success in Higher Education: A Review and Conceptualization]. Revista de Estudios e Investigación en Psicología y Educación, 4, 132-141. >https://doi.org/10.17979/reipe.2017.4.2.3207 Winne, P.H. and Nesbit, J.C. (2010) The Psychology of Academic Achievement. Annual Review of Psychology, 61, 653-678. >https://doi.org/10.1146/annurev.psych.093008.100348 Allen, J.D. (2005) Grades as Valid Measures of Academic Achievement of Classroom Learning. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 78, 218-223. >https://doi.org/10.3200/tchs.78.5.218-223 Brew, E.A., Nketiah, B. and Koranteng, R. (2021) A Literature Review of Academic Performance, an Insight into Factors and Their Influences on Academic Outcomes of Students at Senior High Schools. OALib, 8, 1-14. >https://doi.org/10.4236/oalib.1107423 Sideridis, G. and Alamri, A.A. (2023) Predicting Academic Achievement and Student Absences in High School: The Roles of Student and School Attributes. Frontiers in Psychology, 14, Article 987127. >https://doi.org/10.3389/fpsyg.2023.987127 Singh, A.S. and Masuku, M.B. (2014) Sampling Techniques&Determination of Sample Size in Applied Statistics Research: An Overview. International Journal of Economics, Commerce and Management, 2, 1-22. Kavitha, K., Joshith, V.P. and Sharma, S. (2024) Beyond Text: ChatGPT as an Emotional Resilience Support Tool for Gen Z—A Sequential Explanatory Design Exploration. E-Learning and Digital Media. >https://doi.org/10.1177/20427530241259099 Paramesha, M., Rane, N. and Rane, J. (2024) Enhancing Resilience through Generative Artificial Intelligence Such as ChatGPT. SSRN Electronic Journal. >https://doi.org/10.2139/ssrn.4832533 Caratiquit, K.D. and Caratiquit, L.J.C. (2023) ChatGPT as an Academic Support Tool on the Academic Performance among Students: The Mediating Role of Learning Motivation. Journal of Social, Humanity, and Education, 4, 21-33. >https://doi.org/10.35912/jshe.v4i1.1558 Mwangi, C., Okatcha, F., Kinai, T. and Anthony, I. (2015) Relationship between Academic Resilience and Academic Achievement among Secondary School Students in Kiambu County, Kenya. International Journal of School and Cognitive Psychology, 2, 1-5. Beale, J. (2020) Academic Resilience and Its Importance in Education after COVID-19. Eton Journal for Innovation and Research in Education, 11, 1-67. >https://cirl.etoncollege.com/wp-content/uploads/sites/4/2020/11/Issue-4-2.pdf Ahmed, U., Umrani, W.A., Qureshi, M.A. and Samad, A. (2018) Examining the Links between Teachers Support, Academic Efficacy, Academic Resilience, and Student Engagement in Bahrain. International Journal of Advanced and Applied Sciences, 5, 39-46. >https://doi.org/10.21833/ijaas.2018.09.008 Zuill, Z. (2016) The Relationship between Resilience and Academic Success among Bermuda Foster Care Adolescents. Ph.D. Thesis, Walden University. >https://scholarworks.waldenu.edu/dissertations/2184 Lappe, J.M. (2000) Taking the Mystery Out of Research: Descriptive Correlational Design. Orthopaedic Nursing, 19, 81. Preacher, K.J. and Hayes, A.F. (2008) Contemporary Approaches to Assessing Mediation in Communication Research. In: Hayes, A.F., Slater, M.D. and Snyder, L.B., Eds., The SAGE Sourcebook of Advanced Data Analysis Methods for Communication Research, Sage Publications, Inc., 13-54. >https://doi.org/10.4135/9781452272054.n2 Lupa-Wójcik, I. (2024) Students’ Willingness to Pay for Access to ChatGPT. Euro-pean Research Studies Journal, 27, 730-745. >https://doi.org/10.35808/ersj/3462 Köhler, C. and Hartig, J. (2024) ChatGPT in Higher Education: Measurement Instruments to Assess Student Knowledge, Usage, and Attitude. Contemporary Educational Technology, 16, ep528. >https://doi.org/10.30935/cedtech/15144 Kamoun, F., Ayeb, W.E., Jabri, I., Sifi, S. and Iqbal, F. (2023) Knowledge, Attitude, and Perception Towards ChatGPT among University Students and Faculty: A Preliminary Exploration. ECE Official Conference Proceedings, London, UK, 13-17 July 2023, 247-266. >https://doi.org/10.22492/issn.2188-1162.2023.20 Kamoun, F., El Ayeb, W., Jabri, I., Sifi, S. and Iqbal, F. (2024) Exploring Students’ and Faculty’s Knowledge, Attitudes, and Perceptions Towards ChatGPT: A Cross-Sectional Empirical Study. Journal of Information Technology Education: Research, 23, 4. >https://doi.org/10.28945/5239 Hasan, H.E., Jaber, D., Al Tabbah, S., Lawand, N., Habib, H.A. and Farahat, N.M. (2024) Knowledge, Attitude and Practice among Pharmacy Students and Faculty Members Towards Artificial Intelligence in Pharmacy Practice: A Multinational Cross-Sectional Study. PLOS ONE, 19, e0296884. >https://doi.org/10.1371/journal.pone.0296884 Mudenda, S., Lubinda, R., Kasanga, M., Musakuzi, Z., Mohamed, S. and Mufwambi, W. (2024) Artificial Intelligence: A Knowledge, Attitude, and Practices Survey among Pharmacy Students at the University of Zambia. Creative Education, 15, 2582-2596. >https://doi.org/10.4236/ce.2024.1512157 Acapuyan Jr., A.D. and E. Manaligod, S.I. (2025) Knowledge, Attitude, and Practices Towards ChatGPT of Senior High School Mathematics Learners. International Journal of Research and Scientific Innovation, XII, 558-562. >https://doi.org/10.51244/ijrsi.2025.12050051 Bolici, F., Varone, A. and Diana, G. (2024) Unpopular Policies, Ineffective Bans: Lessons Learned from ChatGPT Prohibition in Italy. >https://aisel.aisnet.org/ecis2024/track04_impactai/track04_impactai/11 Famaye, T., Bailey, C.S., Adisa, I. and Irgens, G.A. (2024) “What Makes ChatGPT Dangerous Is Also What Makes It Special”: High-School Student Perspectives on the Integration or Ban of Artificial Intelligence in Educational Contexts. International Journal of Technology in Education, 7, 174-199. >https://doi.org/10.46328/ijte.651 Xiao, F., Zhu, S.Y. and Xin, W. (2025) Exploring the Landscape of Generative AI (ChatGPT)-Powered Writing Instruction in English as a Foreign Language Education: A Scoping Review. ECNU Review of Education. >https://doi.org/10.1177/20965311241310881 Tiwari, C.K., Bhat, M.A., Khan, S.T., Subramaniam, R. and Khan, M.A.I. (2023) What Drives Students toward ChatGPT? An Investigation of the Factors Influencing Adoption and Usage of ChatGPT. Interactive Technology and Smart Education, 21, 333-355. >https://doi.org/10.1108/itse-04-2023-0061 Duckworth, A.L., Peterson, C., Matthews, M.D. and Kelly, D.R. (2007) Grit: Perseverance and Passion for Long-Term Goals. Journal of Personality and Social Psychology, 92, 1087-1101. >https://doi.org/10.1037/0022-3514.92.6.1087 Halperin, O. and Eldar Regev, O. (2021) Predicting Academic Success Based on Perseverance and Passion for Long-Term Goals (Grit) among Nursing Students: Is There a Cultural Context? Nurse Education Today, 100, Article ID: 104844. >https://doi.org/10.1016/j.nedt.2021.104844 Kozanitis, A., Desbiens, J.F. and Chouinard, R. (2007) Perception of Teacher Support and Reaction towards Questioning: Its Relation to Instrumental Help-Seeking and Motivation to Learn. International Journal of Teaching and Learning in Higher Education, 19, 238-250. Qayyum, A. (2018) Student Help-Seeking Attitudes and Behaviors in a Digital Era. International Journal of Educational Technology in Higher Education, 15, Article No. 17. >https://doi.org/10.1186/s41239-018-0100-7 Chou, C.Y. and Chang, C.H. (2021) Developing Adaptive Help-Seeking Regulation Mechanisms for Different Help-Seeking Tendencies. Educational Technology & Society, 24, 54-66. De Meester, A., Galle, J., Soenens, B. and Haerens, L. (2022) Perseverance in Motor Tasks: The Impact of Different Types of Positive Feedback. Physical Education and Sport Pedagogy, 29, 221-234. >https://doi.org/10.1080/17408989.2022.2054969 Gentzler, A.L., Kerns, K.A. and Keener, E. (2009) Emotional Reactions and Regulatory Responses to Negative and Positive Events: Associations with Attachment and Gender. Motivation and Emotion, 34, 78-92. >https://doi.org/10.1007/s11031-009-9149-x Lipnevich, A.A., MacCann, C., Bertling, J.P., Naemi, B. and Roberts, R.D. (2012) Emotional Reactions toward School Situations. Journal of Psychoeducational Assessment, 30, 387-401. >https://doi.org/10.1177/0734282912449445 Allawan, J.G. (2021) Exploring the Factors Influencing the Performance in Biology of Senior High School Students at University of Mindanao, Philippines. International Journal of Research and Innovation in Social Science, 5, 352-359. >https://doi.org/10.47772/ijriss.2021.5618 Onel, A. and Firat Durdukoca, S. (2019) Identifying the Predictive Power of Biological Literacy and Attitudes toward Biology in Academic Achievement in High School Students. International Online Journal of Educational Sciences, 11, 214-228. >https://doi.org/10.15345/iojes.2019.02.014 Khedekar, S.M. and Magre, S. (2012) A Study of Information and Communication Technology Awareness and Academic Performance of Secondary Students. International Educational E-Journal, 1, 1-11. Amzil, A. (2022) Academic Resilience and Its Relation to Academic Achievement for Moroccan University Students during the Covid19 Pandemic. International Education Studies, 16, 1-7. >https://doi.org/10.5539/ies.v16n1p1 Fru-Ngongban, A.C. (2023) The Impact of Resilience on Students’ Academic Achievement: Case Study of Secondary School Students. Journal Transnational Universal Studies, 1, 206-213. >https://doi.org/10.58631/jtus.v1i5.31 Bi, J., Izadpanah, S., Mohammadi, Z. and Rezaei, Y.M. (2024) Investigating the Impact of Technology-Based Education on Academic Motivation, Academic Perseverance, and Academic Self-Efficacy in English Language Learning Skills. Education and Information Technologies, 29, 20523-20545. >https://doi.org/10.1007/s10639-024-12712-0 Shoffner, M. (2009) Personal Attitudes and Technology: Implications for Preservice Teacher Reflective Practice. Teacher Education Quarterly, 36, 143-161.