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Approaches to Learning and Contract Cheating: Exploring the Mediating Roles of Authorship Perceptions

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Title: Approaches to Learning and Contract Cheating: Exploring the Mediating Roles of Authorship Perceptions
Language: English
Authors: Yinxia Zhang (ORCID 0000-0002-5001-4342), Fengqin Ni
Source: Studies in Higher Education. 2025 50(4):694-708.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 15
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Foreign Countries, Undergraduate Students, Cheating, Plagiarism, Writing (Composition), Cognitive Style, Student Attitudes, Student Behavior, Theses, College Students, Learning Strategies, Questionnaires
Geographic Terms: China
Assessment and Survey Identifiers: Study Process Questionnaire
DOI: 10.1080/03075079.2024.2352055
ISSN: 0307-5079
1470-174X
Abstract: As an undesired learning behavior, contract cheating has its roots in college students' difficulties in engaging in a challenging written assessment. To better understand this process, the study collects multicampus survey data from 910 Chinese undergraduates to explore the effects of deep and surface approaches to learning on contract cheating, focusing on the mediating roles of authorship perceptions. The authorship perceptions are measured with three subfactors: understanding authorship and plagiarism (UAP), authorial approach to writing (AAW), and incorporating others' writing (IOW). Structural equation modeling (SEM) reveals a notable positive direct effect of the surface approach to learning on contract cheating and an insignificant direct effect of the deep approach. The results further report significant indirect effects of both deep and surface approaches to learning on contract cheating via UAP and IOW, while the indirect effects via AAW are both insignificant. These results highlight the importance of providing formal and continuous pedagogical support to enhance their learning, particularly academic writing, in inhibiting contract cheating.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1498284
Database: ERIC
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  Value: <anid>AN0184106891;she01apr.25;2025Apr01.06:16;v2.2.500</anid> <title id="AN0184106891-1">Approaches to learning and contract cheating: exploring the mediating roles of authorship perceptions </title> <p>As an undesired learning behavior, contract cheating has its roots in college students' difficulties in engaging in a challenging written assessment. To better understand this process, the study collects multicampus survey data from 910 Chinese undergraduates to explore the effects of deep and surface approaches to learning on contract cheating, focusing on the mediating roles of authorship perceptions. The authorship perceptions are measured with three subfactors: understanding authorship and plagiarism (UAP), authorial approach to writing (AAW), and incorporating others' writing (IOW). Structural equation modeling (SEM) reveals a notable positive direct effect of the surface approach to learning on contract cheating and an insignificant direct effect of the deep approach. The results further report significant indirect effects of both deep and surface approaches to learning on contract cheating via UAP and IOW, while the indirect effects via AAW are both insignificant. These results highlight the importance of providing formal and continuous pedagogical support to enhance their learning, particularly academic writing, in inhibiting contract cheating.</p> <p>Keywords: Approach to learning; contract cheating; authorship perception; Chinese college student; academic cheating</p> <hd id="AN0184106891-2">Introduction</hd> <p>Contract cheating, also known as ghostwriting by the public, is a subtype of plagiaristic behavior that illustrates college students' submission of written work completed by a third party to obtain academic credit (Clarke and Lancaster [<reflink idref="bib19" id="ref1">19</reflink>]). Due to college students' heavier utilization of the internet and social media, contract cheating is becoming a concern for higher education sectors worldwide, given its historically rising yet underestimated prevalence (Curtis et al. [<reflink idref="bib22" id="ref2">22</reflink>]; Curtis and Clare [<reflink idref="bib21" id="ref3">21</reflink>]; Newton [<reflink idref="bib44" id="ref4">44</reflink>]). However, technology to date is still insufficiently effective in detecting contract cheating on a large scale with a manageable cost (Amigud [<reflink idref="bib2" id="ref5">2</reflink>]; Crook and Nixon [<reflink idref="bib20" id="ref6">20</reflink>]; Lines [<reflink idref="bib41" id="ref7">41</reflink>]). Beyond these technological challenges, contract cheating not only impairs individual learning but also undermines the fairness of assessment and encourages an atmosphere rewarding utterly short-cut learning behaviors.</p> <p>To maintain the quality and integrity of higher education provisions, western practitioners on the national level such as the Quality Assurance Agency in the UK and the Tertiary Education Quality and Standards Agency in Australia have initiated policy agendas and research projects to cope with contract cheating (Bretag et al. [<reflink idref="bib17" id="ref8">17</reflink>]; [<reflink idref="bib18" id="ref9">18</reflink>]). In China, the context where the study is located, according to the <emph>Measures for Cheating Behaviors in Degree Dissertations</emph>, a governmental regulation issued by the Ministry of Education in 2013, students purchasing a dissertation or asking someone else they know to complete the dissertation instead may cause disqualification from applying for the related degree. These measures are included in the Chinese university policies against academic dishonesty.</p> <p>Few studies on contract cheating have focused on non-western contexts (Ahsan, Akbar, and Kam [<reflink idref="bib1" id="ref10">1</reflink>]). Extant literature is reaching a shared understanding that the deterring effectiveness of the straightforward regulative measures appears limited (Amigud and Dawson [<reflink idref="bib3" id="ref11">3</reflink>]) and that it is constructive to perceive contract cheating as an educational issue relating to students' experiences in learning, particularly in writing (Crook and Nixon [<reflink idref="bib20" id="ref12">20</reflink>]; Lines [<reflink idref="bib41" id="ref13">41</reflink>]). Researchers suggest that as an undesired learning behavior, contract cheating has its roots in college students' difficulties in engaging in a challenging written assessment (Ahsan, Akbar, and Kam [<reflink idref="bib1" id="ref14">1</reflink>]).</p> <p>The study takes an educational stance, believing that to achieve a nuanced understanding of the motivators of contract cheating, we should revisit the learning process in which it occurs. We aim to examine the process where students' general ways of engaging in a learning task (i.e. approaches to learning) are translated into an inclination towards contract cheating via their understandings of authorship and ways of writing (i.e. authorship perceptions).</p> <hd id="AN0184106891-3">Literature review</hd> <p></p> <hd id="AN0184106891-4">Contract cheating as a plagiaristic behavior and its correlations with learning experiences</hd> <p>Contract cheating was coined by Clarke and Lancaster ([<reflink idref="bib19" id="ref15">19</reflink>], 1) as 'the submission of work by students for academic credit which the students have paid contractors to write for them.' It is often known as ghostwriting by the public and is considered a unique form of plagiaristic behavior (Lines [<reflink idref="bib41" id="ref16">41</reflink>]). It is gaining prevalence worldwide. As a systematic review of 71 samples identified from 65 studies going back to 1978 reports, a historical average of 3.52% of students admitted to paying someone else to do their work, and in the 13 samples from studies in 2014-2016, the percentage of students self-reporting commercial contract cheating was 15.7%, 'potentially representing 31 million students around the world' (Newton [<reflink idref="bib44" id="ref17">44</reflink>], 1). Contract cheating involves three actors: a student, their university, and a third party (Draper and Newton [<reflink idref="bib25" id="ref18">25</reflink>]). In addition to the widely recognized commercial third parties (i.e. essay mills) where an act of payment happens, recent studies have expanded contract cheating to illustrate the situation of outsourcing assessment work to someone a student knows (i.e. other students, friends, and family) (Amigud and Lancaster [<reflink idref="bib4" id="ref19">4</reflink>]; Awdry and Ives [<reflink idref="bib8" id="ref20">8</reflink>]; Bretag et al. [<reflink idref="bib17" id="ref21">17</reflink>]; Harper et al. [<reflink idref="bib31" id="ref22">31</reflink>]).</p> <p>As an integrated part of the learning process, assessment may influence whether and how a student may engage in contract cheating. A large-scale survey in Australia reports that college students' inclination towards contract cheating is influenced by their perceived characteristics of assessment designs (Bretag et al. [<reflink idref="bib17" id="ref23">17</reflink>]; [<reflink idref="bib18" id="ref24">18</reflink>]). Though there are accounts of contract cheating involving exams (i.e. getting exam answers via online test bank), written assessments have been the major products traded between the students and third parties (Bretag et al. [<reflink idref="bib17" id="ref25">17</reflink>]). Academic writing is an instructional and evaluative tool in higher education (Lavelle and Guarino [<reflink idref="bib39" id="ref26">39</reflink>]). Enhancing literacy in writing should be a critical purpose of college education. Researchers advocate for a multi-pronged and holistic approach that not only focuses on designing authentic, personalized, and professionally-focused written assessments but also cares for students' overall learning experiences (Awdry and Newton [<reflink idref="bib9" id="ref27">9</reflink>]; Bretag et al. [<reflink idref="bib17" id="ref28">17</reflink>]; [<reflink idref="bib18" id="ref29">18</reflink>]; Crook and Nixon [<reflink idref="bib20" id="ref30">20</reflink>]).</p> <p>The effectiveness of plagiarism detection technologies is confined to copy-and-paste plagiarism (Ahsan, Akbar, and Kam [<reflink idref="bib1" id="ref31">1</reflink>]; Curtis and Clare [<reflink idref="bib21" id="ref32">21</reflink>]). The workload of case-by-case detection of contract cheating falls on the shoulders of faculty members, whose vigilance as markers is not always guaranteed (Harper et al. [<reflink idref="bib31" id="ref33">31</reflink>]; Lines [<reflink idref="bib41" id="ref34">41</reflink>]; Medway, Roper, and Gillooly [<reflink idref="bib43" id="ref35">43</reflink>]). The absence of feasible detection strategies may shape students' perceptions of the learning environments as affluent in contract cheating opportunities and low risks of being caught or punished (Curtis and Clare [<reflink idref="bib21" id="ref36">21</reflink>]).</p> <p>To discourage students from contract cheating, a shared understanding among researchers is to perceive contract cheating as an educational matter (rather than a merely administrative or legal issue) and explore its root causes in students' learning experiences (Ahsan, Akbar, and Kam [<reflink idref="bib1" id="ref37">1</reflink>]; Amigud and Dawson [<reflink idref="bib3" id="ref38">3</reflink>]; Awdry and Newton [<reflink idref="bib9" id="ref39">9</reflink>]; Bretag et al. [<reflink idref="bib17" id="ref40">17</reflink>]; Crook and Nixon [<reflink idref="bib20" id="ref41">20</reflink>]). This educational stance is constructive for achieving the goal of enhancing student development. Extant studies have identified several learning-related motivators of contract cheating.</p> <p>For instance, students who hold a product perspective of assessment (Crook and Nixon [<reflink idref="bib20" id="ref42">20</reflink>]) and are under the pressure of avoiding failure and achieving a passing grade (Amigud and Lancaster [<reflink idref="bib4" id="ref43">4</reflink>]; Awdry and Newton [<reflink idref="bib9" id="ref44">9</reflink>]) are often risk-taking and motivated to conduct contract cheating, even when they may be aware of the risks of blackmailing threats from the third-parties (Yorke, Sefcik, and Veeran-Colton [<reflink idref="bib50" id="ref45">50</reflink>]). When engaging in a learning task, students who conduct contract cheating tend to report some negative learning experiences, including lacking self-discipline and perseverance to complete tasks (Amigud and Lancaster [<reflink idref="bib4" id="ref46">4</reflink>]; Rundle, Curtis, and Clare [<reflink idref="bib47" id="ref47">47</reflink>]), lacking academic aptitudes or competence satisfaction (Awdry and Newton [<reflink idref="bib9" id="ref48">9</reflink>]; Rundle, Curtis, and Clare [<reflink idref="bib47" id="ref49">47</reflink>]), perceptions of assessments as unworthy of extra efforts (Amigud and Lancaster [<reflink idref="bib4" id="ref50">4</reflink>]), and dissatisfaction with teaching (i.e. poor understanding of assignment requirements and receiving insufficient feedback) (Bretag et al. [<reflink idref="bib17" id="ref51">17</reflink>]; [<reflink idref="bib18" id="ref52">18</reflink>]). In contrast, positive traits such as high morality, self-control, and motivation to engage in genuine learning may inhibit contract cheating (Rundle, Curtis, and Clare [<reflink idref="bib47" id="ref53">47</reflink>]).</p> <p>Though lacking a firm theoretical standpoint from the psychological or behavioral sciences (Ahsan, Akbar, and Kam [<reflink idref="bib1" id="ref54">1</reflink>]), the evidence combined suggest that contract cheating is an undesired learning behavior relating to a complicated and interwinding set of individual and situational motivators (Bretag et al. [<reflink idref="bib17" id="ref55">17</reflink>]), when a student struggles to meet the requirements for a challenging written assessment (Ahsan, Akbar, and Kam [<reflink idref="bib1" id="ref56">1</reflink>]; Amigud and Dawson [<reflink idref="bib3" id="ref57">3</reflink>]). The difficulties in academic writing have been a cause for copy-and-paste plagiarism among college students (Ellery [<reflink idref="bib28" id="ref58">28</reflink>]). A nuanced understanding of contract cheating from student learning and academic literacy perspectives should be promising to inform pedagogical interventions against this behavior (Crook and Nixon [<reflink idref="bib20" id="ref59">20</reflink>]; Lines [<reflink idref="bib41" id="ref60">41</reflink>]).</p> <hd id="AN0184106891-5">Approaches to learning and plagiaristic behaviors</hd> <p>Approaches to learning describe the general ways students engage in their learning tasks. Based on the work of Marton and Säljö ([<reflink idref="bib42" id="ref61">42</reflink>]), the notion of differentiations between deep and surface approaches to learning has been well examined. The deep approach illustrates one's intrinsic interests and desires to master the subject contents and the utilization of meaning-creating strategies for engaging in learning tasks; in contrast, students adopting the surface approach are motivated by extrinsic and performative goals (i.e. fear of failure, good marks) and tend to apply rote learning strategies for reproducing contents with minimum effort (Biggs, Kember, and Leung [<reflink idref="bib16" id="ref62">16</reflink>]). These descriptions construct the deep and surface approaches as two qualitatively different ways of engaging in learning (Asikainen and Gijbels [<reflink idref="bib7" id="ref63">7</reflink>]), in that the deep approach is adaptive and predicts positive learning behaviors, while the surface approach is maladaptive and may give rise to undesired learning behaviors.</p> <p>To our knowledge of the literature, few studies have focused on the influences of approaches to learning on plagiarism with three exceptions. In the study by Guo ([<reflink idref="bib29" id="ref64">29</reflink>]), the surface approach to learning is proposed to cultivate UK accounting students' habits of academic dishonesty and encourage them to indulge in plagiarism, which is not supported by the results. In the study among UK students (Ballantine, Guo, and Larres [<reflink idref="bib11" id="ref65">11</reflink>]), the correlations of both the deep and surface approaches to learning with plagiarism are insignificant; however, in the case of overall academic cheating (i.e. including plagiarism and cheating on exams), a positive correlation for the surface approach to learning and a negative correlation for the deep approach to learning is significant. In the study by Barbaranelli et al. ([<reflink idref="bib14" id="ref66">14</reflink>]) among Italian students, the correlation between the deep approach to learning and overall academic cheating is negative, while the correlation for the surface approach is insignificant.</p> <p>These rare yet inconsistent findings suggest the necessity of further exploration. Extant literature has described contract cheating as an extrinsically motivated short-cut learning behavior in written assessment (i.e. aiming for a passing grade), for which the level of engagement in the mastery of subject contents and writing skills appears shallow (du Rocher [<reflink idref="bib26" id="ref67">26</reflink>]). It is plausible to speculate the relations between deep and surface approaches to learning and contract cheating.</p> <hd id="AN0184106891-6">The mediating roles of authorship perceptions</hd> <p>The definitive feature of contract cheating is students' impersonation of authorship for a written assessment to which they have no or incomplete contributions. To obtain a nuanced understanding, we focus on the mediating roles of authorship perceptions between approaches to learning and contract cheating. Authorship perceptions describe students' perceptions of authorship, plagiarism, and ways of engaging in writing. The following two lines of research support our proposition.</p> <p>The foremost line of research relates to the authorship perspective, a recent development of the educational strand of studies on plagiarism. These studies suggest that plagiarism is attributable to students' insufficiency in writing skills and experience (Ellery [<reflink idref="bib28" id="ref68">28</reflink>]). Some researchers further emphasize the importance of enhancing students' perceptions of themselves as the authors of their written work to decrease plagiarism (Pittam et al. [<reflink idref="bib46" id="ref69">46</reflink>]). The authorship perspective is theoretically rooted in the notion that writing and identity intersect (Hyland [<reflink idref="bib35" id="ref70">35</reflink>]), which advocates for understanding plagiarism as an intertextuality practice where college students learn to become competent academic writers (Howard [<reflink idref="bib33" id="ref71">33</reflink>]).</p> <p>Pittam et al. ([<reflink idref="bib46" id="ref72">46</reflink>]) initially develop a scale to measure college students' authorship perceptions, namely, the Student Authorship Questionnaire (SAQ). Based on this explorative work, empirical evidence of the associations between authorship perceptions and plagiarism has been accumulating (Ballantine et al. [<reflink idref="bib12" id="ref73">12</reflink>]; Ballantine and Larres [<reflink idref="bib13" id="ref74">13</reflink>]; Ballantine, Guo, and Larres [<reflink idref="bib10" id="ref75">10</reflink>]; Ballantine, Guo, and Larres [<reflink idref="bib11" id="ref76">11</reflink>]; Elander et al. [<reflink idref="bib27" id="ref77">27</reflink>]; Kinder and Elander [<reflink idref="bib37" id="ref78">37</reflink>]). Notably, the studies by Ballantine and colleagues not only revalidate the SAQ among UK and Chinese college students but also test the associations between approaches to learning and plagiarism. These studies support the associations between authorship perceptions and plagiarism, in that students with a higher level of understanding of plagiarism and identification with authorship appear less likely to plagiarize, while students with lower confidence in writing and adopting a pragmatic way of writing (i.e. incorporating others' writing to improve the grade) are inclined to plagiarize.</p> <p>The other line of research is on how approaches to learning are reflected in ways of writing. Based on the landmark work by Marton and Säljö ([<reflink idref="bib42" id="ref79">42</reflink>]), the deep and surface model of understanding learning has become generic in college learning research and has been linked to specific academic tasks such as writing. In an early-stage work, Biggs ([<reflink idref="bib15" id="ref80">15</reflink>]) applies the deep and surface model of learning to analyze college students' process of writing, arguing that there are 'obvious parallels between the surface and deep approaches to learning in general and to writing in particular.' (<reflink idref="bib216" id="ref81">216</reflink>). The deep and surface approaches to writing describe the differentiated process of engaging in a writing task. According to Biggs ([<reflink idref="bib15" id="ref82">15</reflink>]), the writing process is complex, involving demanded attention at multiple levels: thematic, paragraph, sentence, grammatical, and lexical. Those with a deep approach to writing tend to focus on high levels of writing (i.e. thematic level), to discover and clarify new meanings, and to use strategies such as discourse structures and complex revisions. Those with a surface approach to writing tend to focus on low levels of writing (i.e. sentence level) and to use strategies such as listing or reproducing facts.</p> <p>The extension of the deep and surface approaches framework to college writing by Biggs ([<reflink idref="bib15" id="ref83">15</reflink>]) has been developed by Lavelle and colleagues (Lavelle [<reflink idref="bib38" id="ref84">38</reflink>]; Lavelle and Guarino [<reflink idref="bib39" id="ref85">39</reflink>]; Lavelle and Zuercher [<reflink idref="bib40" id="ref86">40</reflink>]). They advance understanding of the deep and surface approaches to writing by introducing the notion that students' intentions may affect their choices of writing strategies and written outcomes. These advances in understanding are reflected in their empirical studies (Lavelle and Guarino [<reflink idref="bib39" id="ref87">39</reflink>]; Lavelle and Zuercher [<reflink idref="bib40" id="ref88">40</reflink>]). In these studies, students with a surface approach to writing have low interest and self-efficacy in writing and tend to engage in writing without understanding the writing process or self-expression. In contrast, students with a deep approach tend to connect writing with personal meanings and identities and fully engage in the writing processes that require information integrations and extensive revisions.</p> <p>To sum up, it can be assumed that contract cheating is influenced by students' understanding of authorship and ways of engaging in writing, which is shaped by their overall ways of engaging in learning tasks.</p> <hd id="AN0184106891-7">The study</hd> <p>The study aims to address two questions: First, what are the direct effects of approaches to learning on contract cheating? Second, would students' authorship perceptions mediate the relations between approaches to learning and contract cheating? The study is located in the Chinese context, focusing on final-year undergraduates' inclination towards contract cheating in the dissertation. In China, a faculty member is often designated as a supervisor for an undergraduate's dissertation writing. It is plagiarism involving dissertations rather than daily written assignments that are strictly forbidden and punished (Zhang, Yin, and Zheng [<reflink idref="bib51" id="ref89">51</reflink>]). Relative to daily written assignments, the dissertation is a transformative, high-stakes, and challenging assessment (Ashwin, Abbas, and McLean [<reflink idref="bib6" id="ref90">6</reflink>]). These realities may shape students' contrasting evaluations of the benefits, costs, and risks of contract cheating regarding daily assignments and dissertations. Therefore, we focused on the dissertation, which may provide targeted explorations of the driving mechanism of contract cheating.</p> <hd id="AN0184106891-8">Methods</hd> <p></p> <hd id="AN0184106891-9">Procedures and participants</hd> <p>Via an online questionnaire survey conducted from June to July 2022, we received valid self-reported responses from 910 final-year undergraduate students from six public universities in Fujian province in southeast China. Guided by the central government's general rules, provincial policies for enhancing quality and integrity in undergraduate dissertations (i.e. the procedures and standards for electronic plagiarism detections, and the severity of penalties applied) are different. This is our primary consideration to conduct a small-scale provincial survey. The other practical reasons were the limited research funds and our relatively easy access to the universities in Fujian. Though we know that online survey often suffers from lower response rates than traditional survey methods (particularly for sensitive topics like contract cheating) (Wu, Zhao, and Fils-Aime [<reflink idref="bib49" id="ref91">49</reflink>]), COVID-19 in China was also a reason for choosing online surveys.</p> <p>To get access to the participants, our research team members first made a list of contacts working as <emph>fudaoyuan</emph> (i.e. the student affairs officer) in the universities in Fujian to help distribute questionnaires. The reason for contacting <emph>fudaoyuan</emph> (instead of the course instructors) is to increase the number of participants. In Chinese universities, a <emph>fudaoyuan</emph> is assigned to a class to attend to students' various non-academic issues since the first year of college, has a close relationship with students, and can get in touch with each student in the class (particularly during the COIVID-19). When making decisions about the data collection sites, we expected the sample to reflect the prestige hierarchy of the Chinese higher education system and consist of participants from various areas of study. Based on these two criteria, we received confirmation of help from contacts in six universities (out of thirty-nine in total in Fujian). Two universities are prestigious, included in the national Double First-Class University Project (Peters and Besley [<reflink idref="bib45" id="ref92">45</reflink>]), and the other four are provincial universities. The average number of final-year undergraduates in 2022 in the six universities was 5788, ranging from 4855 to 6475.</p> <p>With the permission and assistance from our contacts, a link to our questionnaire on Survey Star (i.e. an online survey platform) was sent to the students through WeChat (i.e. a widely-used instant messaging software in China) by our contacts. During the survey distribution, combining the number of students in each contact's class, the link was sent to a rough estimate of 5083 students since we cannot guarantee that every student received the link.</p> <p>Given the ethically sensitive nature of the research topic, the students were fully informed of the principle of voluntary and anonymous participation by our contacts and through the introduction section of the questionnaire. We obtained ethical approval for the survey from the ethical committee of the university with which the authors are affiliated and did not offer incentives for survey participation.</p> <p>At the end of the survey, we received 1265 responses, leading to a rough estimate of the response rate as 24.89%. After screening and excluding those with a large portion of missing answers (i.e. skipping the whole section of items measuring a key studied variable) or patterned answers (i.e. continuously ticking the same value on more than 10 items), 910 valid cases remained.</p> <p>The valid sample constituted 2.62% of the final-year undergraduate population in the surveyed universities, with the number of valid cases for each university ranging from 99 to 318. Demographic information of the sample was as follows: the mean of chronological age was 22.13 with a standard deviation of 0.88; 262 (28.8%) were male, and 648 (71.2%) were female; 328 (36.0%) were from hard-disciplines (i.e. mathematics, computer science, civil engineering, and physics), and 582 (64.0%) were from soft-disciplines (i.e. Chinese literature, education, psychology, and management); 199 (21.9%) studied in two prestige universities, and 711 (78.1%) were from the other four provincial universities.</p> <hd id="AN0184106891-10">Measures</hd> <p></p> <hd id="AN0184106891-11">Contract cheating</hd> <p>We used three items to measure contract cheating on a 6-point Likert scale (1 = strongly disagree, 6 = strongly agree). The items respectively describe whether the participant once considered asking a close friend, a family member, or an essay mill accessed via the internet to write the dissertation for them.</p> <hd id="AN0184106891-12">The revised two-factor study process questionnaire</hd> <p>We revalidated the 20-item revised two-factor Study Process Questionnaire (SPQ) (Biggs, Kember, and Leung [<reflink idref="bib16" id="ref93">16</reflink>]) to measure deep and surface approaches to learning on a 6-point Likert scale (1 = strongly disagree, 6 = strongly agree). The SPQ has a hierarchical dimensionality consisting of four 5-item subscales: deep motive, deep strategy, surface motive, and surface strategy.</p> <hd id="AN0184106891-13">Student authorial questionnaire</hd> <p>We revalidated the 18-item 6-factor Student Authorship Questionnaire (SAQ) (Pittam et al. [<reflink idref="bib46" id="ref94">46</reflink>]) to measure authorship perceptions on a 6-point Likert scale (1 = strongly disagree, 6 = strongly agree). The original SAQ focuses on daily assignments. Given our emphasis on the dissertation, we replaced the word 'written assignment' in the original scale with 'dissertation.' Participants were instructed to answer the survey items based on their dissertation writing experiences.</p> <hd id="AN0184106891-14">Controlled variables</hd> <p>There were five demographic variables: gender, age, grade, area of study, and institution prestige. Except for the chronological age and overall grade during college (1 = fail, 5 = excellent), the other variables were coded as binary variables: for gender, female = 0 and male = 1; for the area of study, hard-discipline = 0 and soft-discipline = 1; for institution prestige, average institution = 0 and prestige institution = 1.</p> <hd id="AN0184106891-15">Data analysis</hd> <p>Firstly, we screened the data by checking each participant's responses and deleted invalid cases. The missing value analyses revealed no variable with 5% or more missing data which were calculated using the expectation-maximization algorithm. Then, we used confirmatory factor analyses (CFA) with Mplus 7.0 to test construct validity. Descriptive statistics, Pearson correlations, and Cronbach's alpha coefficients were calculated. Finally, we performed SEM analyses using the maximum likelihood estimation and bootstrapping methods (Hayes [<reflink idref="bib32" id="ref95">32</reflink>]). We used several indices to indicate the robustness of fit (Hu and Bentler [<reflink idref="bib34" id="ref96">34</reflink>]): comparative fit index (CFI) > 0.90, Tucker-Lewis index (TLI) > 0.90, root mean square error of approximation (RMSEA) < 0.08, Standardized Root Mean Squared Residual (SRMR) < 0.08.</p> <hd id="AN0184106891-16">Results</hd> <p></p> <hd id="AN0184106891-17">Construct validity</hd> <p>Table 1 summarizes the CFA results, supporting the utilization of a refined 16-item 2-factor model of approaches to learning and a 16-item 3-factor model of authorship perceptions in the following analyses. As the results suggest, both the first-order 4-factor and 2-factor models of the original 20-item Study Process Questionnaire yield unsatisfactory levels of fit. After removing four items with a factor loading lower than the cut-off value of 0.50 from the scale, both the 4-factor and 2-factor models achieve satisfactory levels of fit. Given its relatively better indices of fit (χ<sups>2</sups> = 644.23, df = 103, <emph>p</emph> < 0.001; RMSEA = 0.075; CFI = 0.928; TLI = 0.912; SRMR = 0.051) and our attempt to construct a parsimonious model, we chose the 16-item 2-factor model.</p> <p>Table 1. Confirmatory factor analyses results of the measures.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>χ<sup>2</sup></td><td>df</td><td><bold><italic>p</italic></bold></td><td>RMSEA</td><td>CFI</td><td>TLI</td><td>SRMR</td></tr></thead><tbody><tr><td><bold>Study Process Questionnaire</bold></td><td char="." /><td /><td /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>Original 20-item 2-factor model</td><td char=".">1597.46</td><td char=".">169</td><td>< 0.001</td><td char=".">0.095</td><td char=".">0.851</td><td char=".">0.827</td><td char=".">0.085</td></tr><tr><td>Original 20-item 4-factor model</td><td char=".">1524.21</td><td char=".">164</td><td>< 0.001</td><td char=".">0.096</td><td char=".">0.843</td><td char=".">0.824</td><td char=".">0.085</td></tr><tr><td>Refined 16-item 2-factor model</td><td char=".">644.23</td><td char=".">103</td><td>< 0.001</td><td char=".">0.075</td><td char=".">0.928</td><td char=".">0.912</td><td char=".">0.051</td></tr><tr><td>Refined 16-item 4-factor model</td><td char=".">594.46</td><td char=".">98</td><td>< 0.001</td><td char=".">0.076</td><td char=".">0.922</td><td char=".">0.909</td><td char=".">0.052</td></tr><tr><td><bold>Student Authorship Questionnaire</bold></td><td char="." /><td /><td /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>Original 18-item 6-factor model</td><td char=".">953.84</td><td char=".">119</td><td>< 0.001</td><td char=".">0.095</td><td char=".">0.838</td><td char=".">0.787</td><td char=".">0.107</td></tr><tr><td>Refined 16-item 3-factor model</td><td char=".">550.16</td><td char=".">101</td><td>< 0.001</td><td char=".">0.070</td><td char=".">0.911</td><td char=".">0.904</td><td char=".">0.053</td></tr></tbody></table> </ephtml> </p> <p>We revalidated the Student Authorship Questionnaire (SAQ), given the poor data fit of the original 6-factor model. After randomly splitting the data set into two halves, we performed an exploratory factor analysis (EFA) using the principal component method with varimax rotation (<emph>N</emph> = 455) and then conducted a CFA (<emph>N</emph> = 455). The EFA yielded a 3-factor solution with eigenvalues greater than 1.0 for each factor, accounting for 52.09% of the total variance. We deleted two items due to factor loading lower than 0.50. The CFA suggests that the 3-factor model fits the data well (χ<sups>2</sups> = 550.16, df = 101, <emph>p</emph> < 0.001; RMSEA = 0.070; CFI = 0.911; TLI = 0.904; SRMR = 0.053). The 3-factor solution coincides with the study among Chinese college students (Ballantine et al. [<reflink idref="bib12" id="ref97">12</reflink>]). We named the three subfactors as follows: understanding authorship and plagiarism (UAP, 5-item), authorial approach to writing (AAW, 7-item), and incorporating others' writing (IOW, 4-item).</p> <p>Table 2 illustrates acceptable levels of construct validity. Every subfactor has an average variance extracted (AVE) value greater than the 0.50 threshold and a composite reliability value higher than the 0.70 threshold (Hair et al. [<reflink idref="bib30" id="ref98">30</reflink>]), suggesting acceptable convergent validity. Discriminant validity is present if the square root of the AVE is greater than the correlation between constructs (Hair et al. [<reflink idref="bib30" id="ref99">30</reflink>]). The square root of the AVE of each subfactor is higher than their respective correlations, confirming the discriminant validity.</p> <p>Table 2. Results of construct convergent and discriminate validity.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>AVE</td><td>Square root of AVE</td><td><bold>Correlation</bold></td><td>Composite reliability</td></tr></thead><tbody><tr><td><bold>Study Process Questionnaire</bold></td><td char="." /><td char="." /><td>DA</td><td char="." /></tr><tr><td>Deep approach to learning (DA)</td><td char=".">0.504</td><td char=".">0.710</td><td>-</td><td char=".">0.889</td></tr><tr><td>Surface approach to learning (SA)</td><td char=".">0.507</td><td char=".">0.712</td><td char=".">0.047</td><td char=".">0.890</td></tr><tr><td><bold>Student Authorship Questionnaire</bold></td><td char="." /><td char="." /><td>UAP</td><td>AAW</td><td char="." /></tr><tr><td>Understanding authorship and plagiarism (UAP)</td><td char=".">0.523</td><td char=".">0.723</td><td>-</td><td /><td char=".">0.845</td></tr><tr><td>Authorial approach to writing (AAW)</td><td char=".">0.508</td><td char=".">0.713</td><td char=".">0.539</td><td>-</td><td char=".">0.877</td></tr><tr><td>Incorporating others' writing (IOW)</td><td char=".">0.548</td><td char=".">0.740</td><td>−0.087</td><td>0.251</td><td char=".">0.824</td></tr></tbody></table> </ephtml> </p> <p>1 Note: average variance extracted (AVE)</p> <hd id="AN0184106891-18">Descriptive statistics, correlations, and reliability</hd> <p>Table 3 summarizes the descriptive statistics, Pearson correlations, and reliability coefficients. The participants indicated a low inclination towards contract cheating and a dominating deep approach to learning relative to a surface approach. Except for the deep approach to learning, contract cheating correlates with the surface approach to learning and the three subfactors of authorship perceptions. The deep and surface approaches to learning correlate with the three subfactors of authorship perceptions. Gender, grade, and area of study correlate with contract cheating and enter the following SEM analyses. The Cronbach's alpha coefficients in the parentheses suggest satisfactory levels of reliability for the studied variables.</p> <p>Table 3. Descriptive statistics, Pearson correlations, and reliability (<emph>N</emph> = 910).</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td /><td>1</td><td>2</td><td>3</td><td>4</td><td>5</td><td>6</td><td>7</td><td>8</td><td>9</td><td>10</td><td>11</td></tr></thead><tbody><tr><td>1</td><td>Gender</td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>2</td><td>Age</td><td char=".">0.046</td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>3</td><td>Grade of study</td><td char=".">−0.035</td><td char=".">−0.029</td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>4</td><td>Area of study</td><td char=".">−0.079*</td><td char=".">0.038</td><td char=".">−0.003</td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>5</td><td>Institution prestige</td><td char=".">−0.043</td><td char=".">−0.081*</td><td char=".">0.057</td><td char=".">−0.151**</td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>6</td><td>DA</td><td char=".">0.063</td><td char=".">0.071*</td><td char=".">0.127**</td><td char=".">−0.073*</td><td char=".">−0.039</td><td char=".">(0.89)</td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>7</td><td>SA</td><td char=".">0.165**</td><td char=".">−0.068*</td><td char=".">−0.086*</td><td char=".">−0.110**</td><td char=".">−0.013</td><td char=".">0.047</td><td char=".">(0.89)</td><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>8</td><td>UAP</td><td char=".">−0.023</td><td char=".">0.021</td><td char=".">0.163**</td><td char=".">−0.036</td><td char=".">0.075*</td><td char=".">0.355**</td><td char=".">−0.081*</td><td char=".">(0.84)</td><td char="." /><td char="." /><td char="." /></tr><tr><td>9</td><td>AAW</td><td char=".">0.035</td><td char=".">0.009</td><td char=".">0.054</td><td char=".">−0.049</td><td char=".">0.013</td><td char=".">0.504**</td><td char=".">0.196**</td><td char=".">0.539**</td><td char=".">(0.87)</td><td char="." /><td char="." /></tr><tr><td>10</td><td>IOW</td><td char=".">0.138**</td><td char=".">−0.002</td><td char=".">−0.121**</td><td char=".">−0.080*</td><td char=".">−0.088**</td><td char=".">0.134**</td><td char=".">0.557**</td><td char=".">−0.087**</td><td char=".">0.251**</td><td char=".">(0.82)</td><td char="." /></tr><tr><td>11</td><td>Contract cheating</td><td char=".">0.154**</td><td char=".">−0.004</td><td char=".">−0.097**</td><td char=".">−0.089**</td><td char=".">−0.009</td><td char=".">0.060</td><td char=".">0.435**</td><td char=".">−0.109**</td><td char=".">0.132**</td><td char=".">0.421**</td><td char=".">(0.88)</td></tr><tr><td /><td>Mean</td><td char=".">0.29</td><td char=".">22.13</td><td char=".">3.68</td><td char=".">0.64</td><td char=".">0.22</td><td char=".">4.433</td><td char=".">3.362</td><td char=".">5.048</td><td char=".">4.525</td><td char=".">3.359</td><td char=".">1.839</td></tr><tr><td /><td>Standard deviation</td><td char=".">0.453</td><td char=".">0.882</td><td char=".">0.966</td><td char=".">0.480</td><td char=".">0.414</td><td char=".">0.766</td><td char=".">1.021</td><td char=".">0.614</td><td char=".">0.594</td><td char=".">1.095</td><td char=".">1.206</td></tr></tbody></table> </ephtml> </p> <p>2 Note：Gender: female = 0, male = 1; Grade: fail = 1, excellent = 5; Area of study: hard-discipline = 0, soft-discipline = 1; Institution prestige: average institution = 0, prestige institution = 1; Cronbach's alpha coefficients are listed in the parentheses; * <emph>p</emph> <.05, **<emph>p</emph> <.01, 2-tailed.</p> <hd id="AN0184106891-19">SEM analyses</hd> <p>We performed the SEM with the maximum likelihood estimation method to examine the direct and indirect effects of approaches to learning on contract cheating. The SEM results (Figure 1) show acceptable data fit (χ<sups>2</sups> = 2448.09, df = 650, <emph>p</emph> < 0.001; RMSEA = 0.063; CFI = 0.914; TLI = 0.903; SRMR = 0.064), and the amount of explained variance of contract cheating is 29.6%.</p> <p>Graph: Figure 1. The SEM results show indirect effects of the deep and surface approaches to learning (DA, SA) on contract cheating (CC) via the authorship perceptions (UAP, AAW, and IOW), controlling for gender, grade, and area of study. Note: The dotted lines represent insignificant paths; *p <.05, **p <.01, ***p <.001, 2-tailed.</p> <p>We used the bootstrapping method to test the mediation effects. This method is gaining efficacy since it can detect indirect effects with greater sensitivity without emphasizing a significant direct effect as a prerequisite required in the traditional causal steps approach (Hayes [<reflink idref="bib32" id="ref100">32</reflink>]). As Zhao, Lynch, and Chen ([<reflink idref="bib52" id="ref101">52</reflink>], 205) suggest, 'The only requirement for mediation is the indirect effect of a ⅹ b be significant.' They propose three types of mediation: complementary mediation means both direct and indirect effects exist and point in the same direction; competitive mediation means both direct and indirect effects exist and point in opposite directions; indirect-only mediation means indirect effect exists while direct effect does not.</p> <p>Controlling for the influences of gender, grade, and area of study on contract cheating, we used a bootstrapping resample of 1,000 to test the mediation effect with the bias-corrected method and 95% confidence interval. An indirect effect is significant if zero is not within the lower and upper bounds of the 95% confidence interval (Hayes [<reflink idref="bib32" id="ref102">32</reflink>]). Table 4 summarizes the results.</p> <p>Table 4. Total, direct, and indirect effects predicting contract cheating.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td>Model pathways</td><td>Estimated standardized effect</td><td>Bias-corrected 95% confidence interval</td><td><italic>p</italic></td></tr></thead><tbody><tr><td><bold>Total effect</bold></td><td char="." /><td /><td char="." /></tr><tr><td>DA→CC</td><td char=".">0.062</td><td char=".">[−0.012, 0.135]</td><td char=".">0.102</td></tr><tr><td>SA→CC</td><td char=".">0.478</td><td char=".">[0.414, 0.543]</td><td char=".">< 0.001</td></tr><tr><td><bold>Direct effect</bold></td><td char="." /><td /><td char="." /></tr><tr><td>UAP→CC</td><td char=".">−0.124</td><td char=".">[−0.397, – 0.032]</td><td char=".">0.019</td></tr><tr><td>AAW→CC</td><td char=".">0.093</td><td char=".">[−0.082, 0.470]</td><td char=".">0.141</td></tr><tr><td>IOW→CC</td><td char=".">0.243</td><td char=".">[0.248, 0.594]</td><td char=".">< 0.001</td></tr><tr><td>DA→CC</td><td char=".">0.022</td><td char=".">[−0.088, 0.132]</td><td char=".">0.701</td></tr><tr><td>SA→CC</td><td char=".">0.287</td><td char=".">[0.198, 0.375]</td><td char=".">< 0.001</td></tr><tr><td><bold>Indirect effect</bold></td><td char="." /><td /><td char="." /></tr><tr><td>DA→UAP→CC</td><td char=".">−0.054</td><td char=".">[−0.101, – 0.007]</td><td char=".">0.025</td></tr><tr><td>DA→AAW→CC</td><td char=".">0.058</td><td char=".">[−0.018, 0.135]</td><td char=".">0.133</td></tr><tr><td>DA→IOW→CC</td><td char=".">0.035</td><td char=".">[0.015, 0.055]</td><td char=".">0.001</td></tr><tr><td>SA→UAP→CC</td><td char=".">0.015</td><td char=".">[0.001, 0.028]</td><td char=".">0.039</td></tr><tr><td>SA→AAW→CC</td><td char=".">0.019</td><td char=".">[−0.005, 0.044]</td><td char=".">0.149</td></tr><tr><td>SA→IOW→CC</td><td char=".">0.159</td><td char=".">[0.095, 0.222]</td><td char=".">< 0.001</td></tr><tr><td><bold>Total indirect effect</bold></td><td char="." /><td /><td char="." /></tr><tr><td>DA→CC</td><td char=".">0.040</td><td char=".">[−0.035, 0.115]</td><td char=".">0.295</td></tr><tr><td>SA→CC</td><td char=".">0.192</td><td char=".">[0.125, 0.258]</td><td char=".">< 0.001</td></tr></tbody></table> </ephtml> </p> <p>3 Note: bootstrapping resamples <emph>N</emph> = 1,000.</p> <p>The direct effect of the surface approach to learning is notable (β = 0.287, <emph>p</emph> < 0.001), while that of the deep approach to learning is insignificant (β = 0.022, <emph>p</emph> = 0.701). The deep approach has a negative indirect-only mediating effect via UAP (β = – 0.054, <emph>p</emph> = 0.025) and a positive indirect-only mediating effect via IOW (β = 0.035, <emph>p</emph> = 0.001). The indirect effects of the surface approach to learning via UAP (β = 0.015, <emph>p</emph> = 0.039) and IOW (β = 0.159, <emph>p</emph> < 0.001) are both complementary mediations. The total indirect effect of the surface approach to learning is significant (β = 0.192, <emph>p</emph> < 0.001), while that of the deep approach is not (β = 0.040, <emph>p</emph> = 0.295).</p> <hd id="AN0184106891-20">Discussion</hd> <p></p> <hd id="AN0184106891-21">The direct effects of approaches to learning on contract cheating</hd> <p>Extant literature has depicted the deep approach to learning as predictive of positive learning behaviors, whereas the surface approach to learning correlates to negative learning behaviors. As the results indicate, these polarized assumptions are partially supported. Though the deep approach to learning is the relatively dominant inclination relative to the surface approach, its direct effect on contract cheating is insignificant. This result is theoretically unexpected. In contrast, the notable positive direct effect of the surface approach to learning on contract cheating coincides with theoretical expectations. One explanation for the mixed evidence in the study and prior literature (Ballantine, Guo, and Larres [<reflink idref="bib11" id="ref103">11</reflink>]; Barbaranelli et al. [<reflink idref="bib14" id="ref104">14</reflink>]; Guo [<reflink idref="bib29" id="ref105">29</reflink>]) is the different subtypes of cheating behaviors incorporated in each study.</p> <p>It is necessary to revisit the nature of contract cheating and the circumstances where it occurs. Contract cheating in a dissertation in the Chinese context is a high-risk and high-stakes behavior, given the surveillance of a dissertation supervisor throughout the writing process and the severe penalties (i.e. revoking qualification for the degree). It may explain the overall low inclination towards contract cheating in the study. However, when some students consider engaging in contract cheating, the mastery of subject contents and writing skills through the opportunity of dissertation writing, either on a deep or surface level, may appear insignificant to them; what concerns them is to at least obtain a passing grade for the dissertation without necessary inputs of efforts and competences. The performance-oriented motivation may connect contract cheating with a surface approach to learning and render its direct association with a deep approach to learning insignificant.</p> <hd id="AN0184106891-22">The indirect effects of approaches to learning on contract cheating via authorship perception...</hd> <p>The complexity and challenges of academic writing for undergraduate students are illustrated in the multidimensional measures of the authorship perceptions, with cognitive (i.e. UAP) and behavioral elements (i.e. IOW and AAW). As the results suggest, except for the insignificant mediating role of AAW for both deep and surface approaches to learning, authorship perceptions are valid mediators, bridging the associations of deep and surface approaches to learning with contract cheating.</p> <p>UAP describes students' perceptions of themselves as a writer and their understanding of plagiarism. The results indicate a negative association between UAP and contract cheating, coinciding with the suggestion of increasing students' awareness and mastery of academic conventions to avoid plagiarism (Ellery [<reflink idref="bib28" id="ref106">28</reflink>]). Further, the deep approach to learning may decrease contract cheating via increasing UAP, and the surface approach may increase contract cheating via decreasing UAP. These contrasting mediation results partially support the notion of distinctions between deep and surface approaches to learning.</p> <p>IOW is a performance-oriented writing strategy illustrating the incorporation of others' writing to improve grades or indicate competency in writing. The results reveal that the endorsement of both deep and surface approaches to learning may increase contract cheating via increasing IOW. The strong associations of IOW with the surface approach to learning and contract cheating are reasonable, given the shared performance orientation between the two constructs. The positive (though weak) association between the deep approach to learning and IOW is unexpected. This result suggests that students endorsing a deep approach to learning may also use performance-oriented strategies when completing a challenging learning task.</p> <p>AAW describes expressing opinions with one's own words in writing, representing a mastery-oriented writing strategy. The positive (though insignificant) association between AAW and contract cheating is unexpected. One explanation is that contract cheating may be a feasible way for some students who desire to obtain the appearance of authentic writing without actually engaging in the writing themselves. The shared mastery orientation between the deep approach to learning and AAW partially explains their strong association. The unexpected positive (though weak) association between the surface approach to learning and AAW suggests that students endorsing the surface approach may also use mastery-oriented strategies.</p> <p>Taken together, authorship perceptions as parallel mediators enhance the explanatory power of approaches to learning on contract cheating. The results suggest that adopting one dominating approach to learning or writing is not necessarily the antithesis of the endorsement of the other when a student attempts to accomplish a challenging learning task. Chinese students are agentic in their combination of mastery and performance goals and strategies according to the learning tasks and contexts (Ballantine, Guo, and Larres [<reflink idref="bib11" id="ref107">11</reflink>]; Kember [<reflink idref="bib36" id="ref108">36</reflink>]).</p> <p>College students' intentions may influence their choice of writing strategies and the written outcomes (Lavelle and Guarino [<reflink idref="bib39" id="ref109">39</reflink>]). In the study, the final-year undergraduates had two goals: a short-term and performance-oriented goal to obtain the degree and a long-run mastery-oriented goal to harvest personal growth and prepare for future careers by improving their writing ability. From a social desirability perspective (Dompnier, Darnon, and Butera [<reflink idref="bib23" id="ref110">23</reflink>]; [<reflink idref="bib24" id="ref111">24</reflink>]), the mastery goal better accords with the ideology of college learning than the performance goal. It may explain the dominating roles of the deep approach to learning and AAW relative to the surface approach to learning and IOW, respectively. However, from a social utility perspective (Dompnier, Darnon, and Butera [<reflink idref="bib23" id="ref112">23</reflink>]; [<reflink idref="bib24" id="ref113">24</reflink>]), both mastery and performance goals have high and unique values for achieving personal success. The combination of social desirability and utility perspectives may explain the simultaneous utilization of the two seemingly distinct ways of learning and writing.</p> <p>The notable associations of the surface approach to learning with contract cheating needs further exploration. According to Zhao, Lynch, and Chen ([<reflink idref="bib52" id="ref114">52</reflink>]), complementary mediation (i.e. the direct and indirect effects point in the same direction) suggests the possibility of omitted mediators. Beyond the authorship perceptions, future studies may identify other mutually shared yet uninvestigated characteristics between the surface approach to learning and contract cheating.</p> <hd id="AN0184106891-23">Limitations</hd> <p>The study has three limitations. The first limitation is that we measured contract cheating relating to two types of third parties (i.e. commercial essay mills and non-commercial friends and family). Future studies with a qualitative design may identify the motivators of contract cheating relating to each type of third party (Awdry and Ives [<reflink idref="bib8" id="ref115">8</reflink>]). Convenience sampling and self-report surveys have often been used in prior contract cheating research (Curtis et al. [<reflink idref="bib22" id="ref116">22</reflink>]; Newton [<reflink idref="bib44" id="ref117">44</reflink>]). The study also suffers from these limitations. Specifically, the second limitation relates to the generalizability of our findings. Though our sample reflects the overall demographic structure of the Chinese undergraduate population, its convenience (i.e. getting access to participants through personal contacts) and small-scale nature (i.e. confining to one Chinese province) calls for caution in interpreting the findings. Future research may utilize a large-scale, nationwide, and random sampling design. The third limitation is the social desirability bias relating to the self-report method, which may cause contract cheating to be under-reported (Curtis et al. [<reflink idref="bib22" id="ref118">22</reflink>]; Newton [<reflink idref="bib44" id="ref119">44</reflink>]). Future research with self-report methods may control for social desirability (Schmelkin et al. [<reflink idref="bib48" id="ref120">48</reflink>]) or include the incentivised truth-telling method (Curtis et al. [<reflink idref="bib22" id="ref121">22</reflink>]).</p> <hd id="AN0184106891-24">Practical implications</hd> <p>The study has two implications. The foremost implication is for the teachers to undermine students' inclination towards a surface approach to learning. This advice derives from the notable associations between the surface approach and contract cheating. College students' approach to learning is becoming stable yet still malleable and shaped by the learning environments created by the teacher. Deemphasizing the importance of grades and peer competitions may help decrease the incentive value of cheating as a viable short-cut in most cases; meanwhile, teaching methods that encourage students to utilize critical thinking and metacognition to work on a series of well-designed learning tasks to reach a point of genuine mastery of materials and skills, are applicable for enhancing the deep approach to learning (Anderman and Koenka [<reflink idref="bib5" id="ref122">5</reflink>]; Barbaranelli et al. [<reflink idref="bib14" id="ref123">14</reflink>]; du Rocher [<reflink idref="bib26" id="ref124">26</reflink>]).</p> <p>The second implication is for the teachers to actively engage in students' writing process to provide continuous support. Our results suggest that facilitating correct cognition of writing (i.e. understanding plagiarism and expected ways of writing, as measured by UAP and AAW) is necessary yet insufficient in inhibiting plagiarism. Familiarizing students with academic conventions, cultivating academic skills, and providing detailed feedback are suggested (Crook and Nixon [<reflink idref="bib20" id="ref125">20</reflink>]; du Rocher [<reflink idref="bib26" id="ref126">26</reflink>]; Lines [<reflink idref="bib41" id="ref127">41</reflink>]). The whole-process guidance may relieve students' stress in writing, enhance the student-teacher relationship, and make contract cheating less convenient (Ahsan, Akbar, and Kam [<reflink idref="bib1" id="ref128">1</reflink>]; Awdry and Newton [<reflink idref="bib9" id="ref129">9</reflink>]; Bretag et al. [<reflink idref="bib17" id="ref130">17</reflink>]; [<reflink idref="bib18" id="ref131">18</reflink>]; Harper et al. [<reflink idref="bib31" id="ref132">31</reflink>]).</p> <hd id="AN0184106891-25">Disclosure statement</hd> <p>No potential conflict of interest was reported by the author(s).</p> <hd id="AN0184106891-26">Ethics approval</hd> <p>This study involved human participants in the questionnaire survey. All the participants were fully informed of the voluntary nature of the survey before it begun.</p> <ref id="AN0184106891-27"> <title> References </title> <blist> <bibl id="bib1" idref="ref10" type="bt">1</bibl> <bibtext> Ahsan, K., S. Akbar, and B. Kam. 2022. " Contract Cheating in Higher Education: A Systematic Literature Review and Future Research Agenda." Assessment & Evaluation in Higher Education 47 (4): 523 – 39. https://doi.org/10.1080/02602938.2021.1931660.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref5" type="bt">2</bibl> <bibtext> Amigud, A. 2020. " Cheaters on Twitter: An Analysis of Engagement Approaches of Contract Cheating Services." Studies in Higher Education 45 (3): 692 – 705. https://doi.org/10.1080/03075079.2018.1564258.</bibtext> </blist> <blist> <bibl id="bib3" idref="ref11" type="bt">3</bibl> <bibtext> Amigud, A., and P. Dawson. 2020. " The Law and the Outlaw: Is Legal Prohibition a Viable Solution to the Contract Cheating Problem? " Assessment & Evaluation in Higher Education 45 (1): 98 – 108. https://doi.org/10.1080/02602938.2019.1612851.</bibtext> </blist> <blist> <bibl id="bib4" idref="ref19" type="bt">4</bibl> <bibtext> Amigud, A., and T. Lancaster. 2019. " 246 Reasons to Cheat: An Analysis of Students' Reasons for Seeking to Outsource Academic Work." Computers & Education 134 : 98 – 107. https://doi.org/10.1016/j.compedu.2019.01.017.</bibtext> </blist> <blist> <bibl id="bib5" idref="ref122" type="bt">5</bibl> <bibtext> Anderman, E. M., and A. C. Koenka. 2017. " The Relation Between Academic Motivation and Cheating." Theory Into Practice 56 (2): 95 – 102. https://doi.org/10.1080/00405841.2017.1308172.</bibtext> </blist> <blist> <bibl id="bib6" idref="ref90" type="bt">6</bibl> <bibtext> Ashwin, P., A. Abbas, and M. McLean. 2017. " How Does Completing a Dissertation Transform Undergraduate Students' Understandings of Disciplinary Knowledge? " Assessment & Evaluation in Higher Education 42 (4): 517 – 30. https://doi.org/10.1080/02602938.2016.1154501.</bibtext> </blist> <blist> <bibl id="bib7" idref="ref63" type="bt">7</bibl> <bibtext> Asikainen, H., and D. Gijbels. 2017. " Do Students Develop Towards More Deep Approaches to Learning During Studies? A Systematic Review on the Development of Students' Deep and Surface Approaches to Learning in Higher Education." Educational Psychology Review 29 (2): 205 – 34. https://doi.org/10.1007/s10648-017-9406-6.</bibtext> </blist> <blist> <bibl id="bib8" idref="ref20" type="bt">8</bibl> <bibtext> Awdry, R., and B. Ives. 2021. " Students Cheat More Often from Those Known to Them: Situation Matters More Than the Individual." Assessment & Evaluation in Higher Education 46 (8): 1254 – 68. https://doi.org/10.1080/02602938.2020.1851651.</bibtext> </blist> <blist> <bibl id="bib9" idref="ref27" type="bt">9</bibl> <bibtext> Awdry, R., and P. M. Newton. 2019. " Staff Views on Commercial Contract Cheating in Higher Education: A Survey Study in Australia and the UK." Higher Education 78 (4): 593 – 610. https://doi.org/10.1007/s10734-019-00360-0.</bibtext> </blist> <blist> <bibtext> Ballantine, J., X. Guo, and P. Larres. 2015. " Psychometric Evaluation of the Student Authorship Questionnaire: A Confirmatory Factor Analysis Approach." Studies in Higher Education 40 (4): 596 – 609. https://doi.org/10.1080/03075079.2013.835910.</bibtext> </blist> <blist> <bibtext> Ballantine, J. A., X. Guo, and P. Larres. 2018. " Can Future Managers and Business Executives be Influenced to Behave More Ethically in the Workplace? The Impact of Approaches to Learning on Business Students' Cheating Behavior." Journal of Business Ethics 149 (1): 245 – 58. https://doi.org/10.1007/s10551-016-3039-4.</bibtext> </blist> <blist> <bibtext> Ballantine, J., X. Guo, P. Larres, and M. Yu. 2018. " Chinese Authorial Identity: A Model for Scoring the Student Authorship Questionnaire." Studies in Higher Education 43 (12): 2385 – 97. https://doi.org/10.1080/03075079.2017.1333493.</bibtext> </blist> <blist> <bibtext> Ballantine, J., and P. Larres. 2012. " Perceptions of Authorial Identity in Academic Writing among Undergraduate Accounting Students: Implications for Unintentional Plagiarism." Accounting Education 21 (3): 289 – 306. https://doi.org/10.1080/09639284.2011.650452.</bibtext> </blist> <blist> <bibtext> Barbaranelli, C., M. L. Farnese, C. Tramontano, R. Fida, V. Ghezzi, M. Paciello, and P. Long. 2018. " Machiavellian Ways to Academic Cheating: A Mediational and Interactional Model." Frontiers in Psychology 9 (MAY): 695. https://doi.org/10.3389/fpsyg.2018.00695.</bibtext> </blist> <blist> <bibtext> Biggs, J. B. 1988. " Approaches to Learning and to Essay Writing." In Learning Strategies and Learning Styles., edited by R. R. Schmeck, 185 – 228. New York : Plenum.</bibtext> </blist> <blist> <bibtext> Biggs, J. B., D. Kember, and Y. P. Leung. 2001. " The Revised two-Factor Study Process Questionnaire: R-SPQ-2F." British Journal of Educational Psychology 71 : 133 – 49. https://doi.org/10.1348/000709901158433.</bibtext> </blist> <blist> <bibtext> Bretag, T., R. Harper, M. Burton, C. Ellis, P. M. Newton, P. Rozenberg, S. Saddiqui, and K. van Haeringen. 2019. " Contract Cheating: A Survey of Australian University Students." Studies in Higher Education 44 (11): 1837 – 56. https://doi.org/10.1080/03075079.2018.1462788.</bibtext> </blist> <blist> <bibtext> Bretag, T., R. Harper, K. Rundle, P. M. Newton, C. Ellis, S. Saddiqui, and K. van Haeringen. 2020. " Contract Cheating in Australian Higher Education: A Comparison of Non-University Higher Education Providers and Universities." Assessment & Evaluation in Higher Education 45 (1): 125 – 39. https://doi.org/10.1080/02602938.2019.1614146.</bibtext> </blist> <blist> <bibtext> Clarke, R., and T. Lancaster. 2006. " Eliminating the Successor to Plagiarism? Identifying the Usage of Contract Cheating Sites." Proceedings of the Second International Plagiarism Conference, United Kingdom, Gateshead.</bibtext> </blist> <blist> <bibtext> Crook, C., and E. Nixon. 2021. " How Internet Essay Mill Websites Portray the Student Experience of Higher Education." The Internet and Higher Education 48 : 100775. https://doi.org/10.1016/j.iheduc.2020.100775.</bibtext> </blist> <blist> <bibtext> Curtis, G. J., and J. Clare. 2017. " How Prevalent is Contract Cheating and to What Extent Are Students Repeat Offenders? " Journal of Academic Ethics 15 (2): 115 – 24. https://doi.org/10.1007/s10805-017-9278-x.</bibtext> </blist> <blist> <bibtext> Curtis, G. J., M. McNeill, C. Slade, K. Tremayne, R. Harper, K. Rundle, and R. Greenaway. 2022. " Moving Beyond Self-Reports to Estimate the Prevalence of Commercial Contract Cheating: An Australian Study." Studies in Higher Education 47 (9): 1844 – 56. https://doi.org/10.1080/03075079.2021.1972093.</bibtext> </blist> <blist> <bibtext> Dompnier, B., C. Darnon, and F. Butera. 2009. " Faking the Desire to Learn: A Clarification of the Link between Mastery Goals and Academic Achievement." Psychological Science 20 : 939 – 43. https://doi.org/10.1111/j.1467-9280.2009.02384.x.</bibtext> </blist> <blist> <bibtext> Dompnier, B., C. Darnon, and F. Butera. 2013. " When Performance-Approach Goals Predict Academic Achievement and When They do not: A Social Value Approach." British Journal of Social Psychology 52 (3): 587 – 96. https://doi.org/10.1111/bjso.12025.</bibtext> </blist> <blist> <bibtext> Draper, M. J., and P. M. Newton. 2017. " Defending University Integrity." International Journal for Educational Integrity 13 (1): 1 – 16. https://doi.org/10.1007/s40979-016-0012-z.</bibtext> </blist> <blist> <bibtext> du Rocher, A. R. 2020. " Active Learning Strategies and Academic Self-Efficacy Relate to Both Attentional Control and Attitudes Towards Plagiarism." Active Learning in Higher Education 21 (3): 203 – 16. https://doi.org/10.1177/1469787418765515.</bibtext> </blist> <blist> <bibtext> Elander, J., G. Pittam, J. Lusher, P. Fox, and N. Payne. 2010. " Evaluation of an Intervention to Help Students Avoid Unintentional Plagiarism by Improving Their Authorial Identity." Assessment & Evaluation in Higher Education 35 (1): 157 – 71. https://doi.org/10.1080/02602930802687745.</bibtext> </blist> <blist> <bibtext> Ellery, K. 2008. " Undergraduate Plagiarism: A Pedagogical Perspective." Assessment & Evaluation in Higher Education 33 (5): 507 – 16. https://doi.org/10.1080/02602930701698918.</bibtext> </blist> <blist> <bibtext> Guo, X. 2011. " Understanding Student Plagiarism: An Empirical Study in Accounting Education." Accounting Education 20 (1): 17 – 37. https://doi.org/10.1080/09639284.2010.534577.</bibtext> </blist> <blist> <bibtext> Hair, J. F., W. C. Black, B. J. Babin, and R. E. Anderson. 2010. Multivariate Data Analysis: A Global Perspective. Upper Saddle River, NJ : Pearson Education.</bibtext> </blist> <blist> <bibtext> Harper, R., T. Bretag, C. Ellis, P. Newton, P. Rozenberg, S. Saddiqui, and K. van Haeringen. 2019. " Contract Cheating: A Survey of Australian University Staff." Studies in Higher Education 44 (11): 1857 – 73. https://doi.org/10.1080/03075079.2018.1462789.</bibtext> </blist> <blist> <bibtext> Hayes, A. F. 2009. " Beyond Baron and Kenny: Statistical Mediation Analysis in the New Millennium." Communication Monographs 76 (4): 408 – 20. https://doi.org/10.1080/03637750903310360.</bibtext> </blist> <blist> <bibtext> Howard, R. M. 1995. " Plagiarisms, Authorships, and the Academic Death Penalty." College English 57 (7): 788. https://doi.org/10.58680/ce19959094.</bibtext> </blist> <blist> <bibtext> Hu, L. T., and P. M. Bentler. 1999. " Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives." Structural Equation Modeling: A Multidisciplinary Journal 6 : 1 – 55. https://doi.org/10.1080/10705519909540118.</bibtext> </blist> <blist> <bibtext> Hyland, K. 2002. " Authority and Invisibility: Authorial Identity in Academic Writing." Journal of Pragmatics 34 (8): 1091 – 112. https://doi.org/10.1016/S0378-2166(02)00035-8.</bibtext> </blist> <blist> <bibtext> Kember, D. 2000. " Misconceptions About the Learning Approaches, Motivation and Study Practices of Asian Students." Higher Education 40 : 99 – 121. https://doi.org/10.1023/A:1004036826490.</bibtext> </blist> <blist> <bibtext> Kinder, J., and J. Elander. 2012. " Dyslexia, Authorial Identity, and Approaches to Learning and Writing: A Mixed Methods Study." British Journal of Educational Psychology 82 (2): 289 – 307. https://doi.org/10.1111/j.2044-8279.2011.02026.x.</bibtext> </blist> <blist> <bibtext> Lavelle, E. 1993. " Development and Validation of an Inventory to Assess Processes in College Composition." British Journal of Educational Psychology 63 (3): 489 – 99. https://doi.org/10.1111/j.2044-8279.1993.tb01073.x.</bibtext> </blist> <blist> <bibtext> Lavelle, E., and A. J. Guarino. 2003. " A Multidimensional Approach to Understanding College Writing Processes." Educational Psychology 23 (3): 295 – 305. https://doi.org/10.1080/0144341032000060138.</bibtext> </blist> <blist> <bibtext> Lavelle, E., and N. Zuercher. 2001. " The Writing Approaches of University Students." Higher Education 42 (3): 373 – 91. https://doi.org/10.1023/A:1017967314724.</bibtext> </blist> <blist> <bibtext> Lines, L. 2016. " Ghostwriters Guaranteeing Grades? The Quality of Online Ghostwriting Services Available to Tertiary Students in Australia." Teaching in Higher Education 21 (8): 889 – 914. https://doi.org/10.1080/13562517.2016.1198759.</bibtext> </blist> <blist> <bibtext> Marton, F., and R. Säljö. 1976. " On Qualitative Differences in Learning: I—Outcome and Process." British Journal of Educational Psychology 46 (1): 4 – 11. https://doi.org/10.1111/j.2044-8279.1976.tb02980.x.</bibtext> </blist> <blist> <bibtext> Medway, D., S. Roper, and L. Gillooly. 2018. " Contract Cheating in UK Higher Education: A Covert Investigation of Essay Mills." British Educational Research Journal 44 (3): 393 – 418. https://doi.org/10.1002/berj.3335.</bibtext> </blist> <blist> <bibtext> Newton, P. M. 2018. " How Common is Commercial Contract Cheating in Higher Education and Is it Increasing? A Systematic Review." Frontiers in Education 3 (August): 1 – 18. https://doi.org/10.3389/feduc.2018.00067.</bibtext> </blist> <blist> <bibtext> Peters, M. A., and T. Besley. 2018. " China's Double First-Class University Strategy: 双一流." Educational Philosophy and Theory 50 (12): 1075 – 9. https://doi.org/10.1080/00131857.2018.1438822.</bibtext> </blist> <blist> <bibtext> Pittam, G., J. Elander, J. Lusher, P. Fox, and N. Payne. 2009. " Student Beliefs and Attitudes About Authorial Identity in Academic Writing." Studies in Higher Education 34 (2): 153 – 70. https://doi.org/10.1080/03075070802528270.</bibtext> </blist> <blist> <bibtext> Rundle, K., G. J. Curtis, and J. Clare. 2019. " Why Students Do Not Engage in Contract Cheating." Frontiers in Psychology 10 : 1 – 15. https://doi.org/10.3389/fpsyg.2019.02229.</bibtext> </blist> <blist> <bibtext> Schmelkin, L. P., K. Gilbert, K. J. Spencer, H. S. Pincus, and R. Silva. 2008. " A Multidimensional Scaling of College Students' Perceptions of Academic Dishonesty." The Journal of Higher Education 79 (5): 587 – 607. https://doi.org/10.1080/00221546.2008.11772118.</bibtext> </blist> <blist> <bibtext> Wu, M., K. Zhao, and F. Fils-Aime. 2022. " Response Rates of Online Surveys in Published Research: A Meta-Analysis." Computers in Human Behavior Reports 7 : 100206. https://doi.org/10.1016/j.chbr.2022.100206.</bibtext> </blist> <blist> <bibtext> Yorke, J., L. Sefcik, and T. Veeran-Colton. 2022. " Contract Cheating and Blackmail: A Risky Business? " Studies in Higher Education 47 (1): 53 – 66. https://doi.org/10.1080/03075079.2020.1730313.</bibtext> </blist> <blist> <bibtext> Zhang, Y., H. Yin, and L. Zheng. 2018. " Investigating Academic Dishonesty among Chinese Undergraduate Students: Does Gender Matter? " Assessment & Evaluation in Higher Education 43 (5): 812 – 826. https://doi.org/10.1080/02602938.2017.1411467.</bibtext> </blist> <blist> <bibtext> Zhao, X., J. G. Lynch, and Q. Chen. 2010. " Reconsidering Baron and Kenny: Myths and Truths About Mediation Analysis." Journal of Consumer Research 37 (2): 197 – 206. https://doi.org/10.1086/651257.</bibtext> </blist> </ref> <aug> <p>By Yinxia Zhang and Fengqin Ni</p> <p>Reported by Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib19" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib22" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib21" firstref="ref3"></nolink> <nolink nlid="nl4" bibid="bib44" firstref="ref4"></nolink> <nolink nlid="nl5" bibid="bib20" firstref="ref6"></nolink> <nolink nlid="nl6" bibid="bib41" firstref="ref7"></nolink> <nolink nlid="nl7" bibid="bib17" firstref="ref8"></nolink> <nolink nlid="nl8" bibid="bib18" firstref="ref9"></nolink> <nolink nlid="nl9" bibid="bib25" firstref="ref18"></nolink> <nolink nlid="nl10" bibid="bib31" firstref="ref22"></nolink> <nolink nlid="nl11" bibid="bib39" firstref="ref26"></nolink> <nolink nlid="nl12" bibid="bib43" firstref="ref35"></nolink> <nolink nlid="nl13" bibid="bib50" firstref="ref45"></nolink> <nolink nlid="nl14" bibid="bib47" firstref="ref47"></nolink> <nolink nlid="nl15" bibid="bib28" firstref="ref58"></nolink> <nolink nlid="nl16" bibid="bib42" firstref="ref61"></nolink> <nolink nlid="nl17" bibid="bib16" firstref="ref62"></nolink> <nolink nlid="nl18" bibid="bib29" firstref="ref64"></nolink> <nolink nlid="nl19" bibid="bib11" firstref="ref65"></nolink> <nolink nlid="nl20" bibid="bib14" firstref="ref66"></nolink> <nolink nlid="nl21" bibid="bib26" firstref="ref67"></nolink> <nolink nlid="nl22" bibid="bib46" firstref="ref69"></nolink> <nolink nlid="nl23" bibid="bib35" firstref="ref70"></nolink> <nolink nlid="nl24" bibid="bib33" firstref="ref71"></nolink> <nolink nlid="nl25" bibid="bib12" firstref="ref73"></nolink> <nolink nlid="nl26" bibid="bib13" firstref="ref74"></nolink> <nolink nlid="nl27" bibid="bib10" firstref="ref75"></nolink> <nolink nlid="nl28" bibid="bib27" firstref="ref77"></nolink> <nolink nlid="nl29" bibid="bib37" firstref="ref78"></nolink> <nolink nlid="nl30" bibid="bib15" firstref="ref80"></nolink> <nolink nlid="nl31" bibid="bib216" firstref="ref81"></nolink> <nolink nlid="nl32" bibid="bib38" firstref="ref84"></nolink> <nolink nlid="nl33" bibid="bib40" firstref="ref86"></nolink> <nolink nlid="nl34" bibid="bib51" firstref="ref89"></nolink> <nolink nlid="nl35" bibid="bib49" firstref="ref91"></nolink> <nolink nlid="nl36" bibid="bib45" firstref="ref92"></nolink> <nolink nlid="nl37" bibid="bib32" firstref="ref95"></nolink> <nolink nlid="nl38" bibid="bib34" firstref="ref96"></nolink> <nolink nlid="nl39" bibid="bib30" firstref="ref98"></nolink> <nolink nlid="nl40" bibid="bib52" firstref="ref101"></nolink> <nolink nlid="nl41" bibid="bib36" firstref="ref108"></nolink> <nolink nlid="nl42" bibid="bib23" firstref="ref110"></nolink> <nolink nlid="nl43" bibid="bib24" firstref="ref111"></nolink> <nolink nlid="nl44" bibid="bib48" firstref="ref120"></nolink>
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  Data: Approaches to Learning and Contract Cheating: Exploring the Mediating Roles of Authorship Perceptions
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  Data: <searchLink fieldCode="AR" term="%22Yinxia+Zhang%22">Yinxia Zhang</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-5001-4342">0000-0002-5001-4342</externalLink>)<br /><searchLink fieldCode="AR" term="%22Fengqin+Ni%22">Fengqin Ni</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Studies+in+Higher+Education%22"><i>Studies in Higher Education</i></searchLink>. 2025 50(4):694-708.
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
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  Data: 15
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  Data: 2025
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  Data: Journal Articles<br />Reports - Research
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  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Undergraduate+Students%22">Undergraduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22Cheating%22">Cheating</searchLink><br /><searchLink fieldCode="DE" term="%22Plagiarism%22">Plagiarism</searchLink><br /><searchLink fieldCode="DE" term="%22Writing+%28Composition%29%22">Writing (Composition)</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Style%22">Cognitive Style</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Attitudes%22">Student Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Behavior%22">Student Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Theses%22">Theses</searchLink><br /><searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Strategies%22">Learning Strategies</searchLink><br /><searchLink fieldCode="DE" term="%22Questionnaires%22">Questionnaires</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink>
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  Data: <searchLink fieldCode="SU" term="%22Study+Process+Questionnaire%22">Study Process Questionnaire</searchLink>
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  Data: 10.1080/03075079.2024.2352055
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  Data: 0307-5079<br />1470-174X
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: As an undesired learning behavior, contract cheating has its roots in college students' difficulties in engaging in a challenging written assessment. To better understand this process, the study collects multicampus survey data from 910 Chinese undergraduates to explore the effects of deep and surface approaches to learning on contract cheating, focusing on the mediating roles of authorship perceptions. The authorship perceptions are measured with three subfactors: understanding authorship and plagiarism (UAP), authorial approach to writing (AAW), and incorporating others' writing (IOW). Structural equation modeling (SEM) reveals a notable positive direct effect of the surface approach to learning on contract cheating and an insignificant direct effect of the deep approach. The results further report significant indirect effects of both deep and surface approaches to learning on contract cheating via UAP and IOW, while the indirect effects via AAW are both insignificant. These results highlight the importance of providing formal and continuous pedagogical support to enhance their learning, particularly academic writing, in inhibiting contract cheating.
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  Data: 2026
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  Group: ID
  Data: EJ1498284
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1498284
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/03075079.2024.2352055
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 15
        StartPage: 694
    Subjects:
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Undergraduate Students
        Type: general
      – SubjectFull: Cheating
        Type: general
      – SubjectFull: Plagiarism
        Type: general
      – SubjectFull: Writing (Composition)
        Type: general
      – SubjectFull: Cognitive Style
        Type: general
      – SubjectFull: Student Attitudes
        Type: general
      – SubjectFull: Student Behavior
        Type: general
      – SubjectFull: Theses
        Type: general
      – SubjectFull: College Students
        Type: general
      – SubjectFull: Learning Strategies
        Type: general
      – SubjectFull: Questionnaires
        Type: general
      – SubjectFull: China
        Type: general
      – SubjectFull: Study Process Questionnaire
        Type: general
    Titles:
      – TitleFull: Approaches to Learning and Contract Cheating: Exploring the Mediating Roles of Authorship Perceptions
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Yinxia Zhang
      – PersonEntity:
          Name:
            NameFull: Fengqin Ni
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 0307-5079
            – Type: issn-electronic
              Value: 1470-174X
          Numbering:
            – Type: volume
              Value: 50
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Studies in Higher Education
              Type: main
ResultId 1