Towards an Holistic Framework to Mitigate and Detect Contract Cheating within an Academic Institute—A Proposal

Abstract

There has been a growing number of contract cheating incidents recorded in Australia’s higher education system. Such activities create a significant threat to the validity and integrity of qualifications obtained by students. This paper introduces a conceptual framework to combat contract cheating by compiling the findings on domain analysis, institute-wide policy analysis, and by applying self-efficacy theories. The literature review on domain analysis lays out two state-of-the-art strategies to combat contract cheating: detect and mitigate the opportunities. Policy document analysis sheds some light on existing operating mechanisms for handling contract cheating cases and the gaps need to be addressed. The proposed framework has three tiers: Awareness, Monitoring and Evaluation. At the awareness level, students’ awareness concerning contract cheating is enhanced by several activities, and staff skills are strengthened by professional activities. At the monitoring level, student activities associated with assessments are recorded using a Pre-Designed Template (PDT) and are monitored by analysing the data in three databases; Monitoring database, Academic Integrity breach database, software analysis data. At the evaluation level, the institutional policies, procedures and services related to contract cheating are evaluated and revised on a regular basis, using feedback mechanisms. This holistic approach may discourage contract cheating by increasing the awareness among students, developing professional skills of staff and organising continuous course-wide student monitoring using various databases. Finally, the proposed approach fills the gaps in the existing system by utilising a systematic process to evaluate an institute’s policies, procedures and services.

1. Introduction

Contract cheating is a form of academic misconduct whereby students have their assignments completed by third parties. Recent research reveals that the number of students engaging in contract cheating is rapidly increasing [1,2,3] and threatens the validity and integrity of qualifications obtained by students.

Contract cheating services can be categorised as either commercial or non-commercial, depending on how the assignment is outsourced. Commercial contract cheating occurs when a student recruits a third party to complete their work on a fee-for-service basis. Non-commercial contract cheating occurs when a student’s friends or family complete the work on a non-fee-for-service basis. Subsequently, students submit the assignment claiming it as their own individual work [2,4,5]. Clearly, neither commercial nor non-commercial contract cheating is acceptable and both need to be addressed immediately to prevent unskilled and unqualified graduates entering the work force.

The goal of this paper was to identify strategies to develop a conceptual framework to combat contract cheating. These strategies should involve all stakeholders (staff, students, and administration) in promoting academic integrity in every aspect of an institute. We adopted a two-fold approach. First, we formulated strategies to detect contract cheating and, second, we proposed methods to mitigate the opportunities for students to engage in contract cheating behaviour. Detecting contract cheating is a challenge, and some universities have pursued legal channels to counteract this issue, which is a very costly and time consuming process [6,7]. Hence, educational institutions need to tackle the challenges posed by contract cheating themselves to safeguard the interests of all students and their academic qualifications.

After an extensive literature review and institute-wide policy analysis on the academic integrity process at the institute where we work, the key problems that needed to be addressed by the proposed framework were identified as follows:

• Current institutional policies and procedures indicated that academic misconduct was identified and managed on an assignment-by-assignment basis. There was no transfer of knowledge about patterns and trends from one assignment to another, or from one unit to another, when identifying contract cheating cases. Therefore current approaches lacked sufficient evidence to form pattern analysis on students performance within a single unit or throughout a course. Pattern analysis is crucial for detecting contract cheating cases.
• While there are policies and procedures to handle academic integrity breaches, there is no comprehensive strategy or procedure to consistently handle contract cheating cases.
• Lack of specialised organisational units, such as an Academic Integrity Office (AIO), to handle contract cheating cases and ensure consistency within the institute needed to be addressed.

This paper presents a practical framework to minimise contract cheating cases within an institute. The framework was developed on the findings of contract cheating domain analysis (performed by literature review), institute-wide policy analysis and also the compilation of self-efficacy theories. The outline of the paper is as follows: Section 2 outlines the potential strategies to detect contract cheating. Section 3 lays out the schemes to minimise opportunities for contract cheating. Section 4 outlines the proposed framework to mitigate and detect contract cheating in an educational setting. Finally, Section 5 presents the conclusion, limitations and possible future directions. All of the acronyms used in this paper are presented in a Table in the Abbreviations Section.

2. Determining Strategies to Detect Contract Cheating

This section presents some prospective approaches that could be applied to detect contract cheating. Three viewpoints were selected to discuss the strategies to detect contract cheating: staff upskilling, pattern analysis and assignment design.

2.1. Staff Upskilling

In this section, we outline strategies to upskill staff and expand their capabilities in detecting and mitigating contract cheating, mainly focusing on professional training and research in academic integrity.

2.1.1. Staff Training to Improve Accuracy

Academic staff play a crucial role in detecting contract cheating. They, therefore, must be provided with adequate training to develop the skills needed to perform this role. These skills are additional to discipline-related skills and can be obtained by professional training [3,6,8,9]. Academic research literature indicates that most academics encounter some form of contract cheating [3,6,8], and, hence, they need to have appropriate skills to identify various types of potential contract cheating [9]. However, an academic’s ability to detect contract cheating is very difficult to evaluate. In [8], a workshop was conducted in order to improve markers’ accuracy in detecting contract cheating and to compare untrained markers’ accuracy with that of trained markers’ accuracy. It was reported that the accuracy of untrained markers’ detection was lower in terms of sensitivity and specificity. The untrained markers were unable to detect contract cheating 42% of the time, while the trained markers missed only 18%. The study concluded that marker training could have an impact on detecting contract cheating. Familiarity of markers with patterns in potential cases, updating markers with current trends, and sharing working knowledge and good practices in identifying academic misconduct were pragmatic approaches to improve awareness among academics. These skill development activities could be organised during staff meetings and professional training.

Staff perception of contract cheating is lacking [10]. The following are some of the challenges academic staff face today, which need to be addressed, as they are the major stakeholders who could implement the strategies to detect contract cheating.

• The lack of familiarity with the patterns and trends of potential contract cheating cases [8,11]. For example, markers’ detection rates might improve if they were familiar with the irregularities evident in certain sections of a report, the body of the text or in reference materials.
• The time constraints faced by markers to complete grading and feedback. If markers evaluate students while students are taking their class, they need sufficient time to interview students to confirm the assignment was their own genuine effort. An adequate amount of time needs to be allocated for grading and further investigation to detect contract cheating, so that markers can apply various strategies if there are suspicious cases [12].
• Difficulty and seriousness of the breach. There is lack of consistency in deciding a penalty, due to difficulty in identifying the seriousness of the breach in the contract cheating [3,13]. Therefore, there is a need for consistent and unified approaches.

The above issues (trend analysis, time investment, and skills required), could be addressed through the development of a specialised organisational unit, such as an Academic Integrity Office (AIO). This proposed centralised unit would be responsible for developing and implementing institutional academic integrity policies and procedures, as well as monitoring, investigating and reporting on academic integrity breaches [11,14,15]. The AIO would also provide training, resources and tools for staff and students to develop their knowledge and understanding of academic integrity best practices. These resources could be shared with staff and students by uploading on to a centralised location (possibly a website). The authors in [16] published a practical toolkit to develop professional practice for teachers in higher education settings.

2.1.2. High-Profile Research to Educate Academics

Promoting and supporting academics to conduct research on academic integrity, including contract cheating, is another strategy to enhance their knowledge of trends and patterns and the technological advancements in the contract cheating domain. Then, the outcomes from these research works could be shared with other staff to enhance detection skills. The research activities would also encourage academics to design and implement innovative approaches to detect this serious academic issue [17,18].

2.2. Pattern Analysis

Another strategy to detect contract cheating is to utilise pattern and trend analysis on students’ writing styles and their performance in assessments. This analysis could be performed using software tools or manually by instructors or specialised administrative staff.

2.2.1. Software Analysis

There are different software tools available in the academic industry for text-matching but only a few software tools are available to detect contract cheating indirectly. However, there is no software tool available in the industry that can detect contract cheating directly.

Text-matching tools, such as Turnitin, which are integrated into Learning Management Systems (LMS), play a significant role in identifying plagiarism. Ouriginal is another pattern-matching system with some additional features, in that it compares work submitted by students with online documents, regardless of language [19]. Ouriginal has been acquired by Turnitin. Furthermore, SafeAssign [20] is a tool provided by Blackboard LMS to evaluate the originality of a document by comparing students’ submitted work with the existing resources, including a set of academic papers. The originality report provides opportunities for students and staff to identify how to correctly credit sources. Cadmus [21] is another assessment submission platform, accessed through the LMS, which checks the originality of the documents submitted. The web-based software tool iThenticate [22] can identify plagiarism and copyright issues. It scans the uploaded document against millions of web pages and scholarly articles. This detects issues in citation and attribution in research papers but cannot be used to detect contract cheating. Furthermore, there are some open source and subscription tools provided by Deborah Weber-Wul [23] for plagiarism detection. CitePlag [24] is a citation-based plagiarism detection tool, which uses co-citation proximity analysis methodology to detect instances of similarity. This quick review indicates that there are a variety of software tools available for text-matching, but these software tools are not designed to detect contract cheating.

Some software tools are available to do pattern analysis and can be used by non-academic or specialised staff for further investigation. An additional feature in Turnitin called Authorship  for  Investigator [25,26] can assist investigators to gather evidence for further investigation. Nevertheless, it does not identify contract cheating directly. This feature can be utilised by an AIO for an additional investigation to generate evidence. Further investigations on using advanced tools for contract cheating is conducted in [27,28,29,30]. In [27], Dawson et al. analysed the use of the alpha version of the authorship investigation tool on Turnitin for identifying effectiveness in detecting contract cheating, and reported that when the markers used this tool, the detection rate increased from 48% to 59%. In a pilot study, Ison [28] evaluated the use of free commercial (off-the-shelf) stylometry software for detecting contract cheating and found that stylometry software supported the detection of anomalies in authorship. Free stylometry software used for this study were Signature Stylometry System 1.0, Java Graphical Authorship Attribution Program, and JStylo Authorship Attribution Framework v1.2. Trezise et al. [29] utilised learning analytics to detect whether students were submitting new writing or transcribing text. Contract cheating is impossible to detect only with software tools and there is a need of manual intervention by the academic assessors and an AIO.

2.2.2. Assessor Analysis

Since available software tools alone are not capable of detecting contract cheating, academic staff and an AIO can play important roles in identifying cheating assignments. Assessors need to observe various aspects to detect contract cheating cases. First, unusual patterns of student performance can be useful to identify contract cheating [27,28]. The student’s writing style needs to be consistent from assignment to assignment throughout the degree, in forum posts and in emails, and it should not go beyond the capabilities of the student. Assessors can use their observational skills, academic judgement, intuition and considerable manual analysis to determine irregularities in the submitted assignments.

Monitoring students’ academic progress plays a crucial role in detecting contract cheating. The assessors can record their observations on students’ assignment progress in a Pre-Designed Template (PDT) regularly during unit delivery, which is discussed in Section 4.1.2. Experienced unit coordinators and tutors can incorporate their subject knowledge and experience into these template designs. Researchers in [31] developed a simple model to highlight the importance of including manual analysis in electronic academic integrity breaches. The tutor could enter a numeric grade, after assessing the student’s progress. Authors in [32] discussed a concept called “One-Minute Paper” which was originally published by [33]. They highlighted the importance of checking the progress of learning. In this technique, during the last few minutes of the class, students are asked to respond briefly to a variation of the two questions; “what was the most important thing you learned during this class?” and “what important questions remain unanswered?”. Students are supposed to write their answers and submit them (Half-Sheet Response). This One-Minute Paper technique is a quick and extremely simple way to have a sense of their learning, and can easily be adopted to monitor student learning and understanding about the assignment topics, in online and face-to-face classrooms.

A more comprehensive description of how to identify unusual patterns between supervised and unsupervised assignments can be found in [34]. In this research study, different grade bands were assigned to monitor the performance differences in marks in supervised and unsupervised assignments [34]. Academic staff could monitor student performance within the units they teach; however, the support of specialised administrative staff is necessary to see students’ overall performance across the degree programme.

2.2.3. Specialised Administrative Staff Analysis

Specialised administrative staff analysis refers to the analysis conducted by academic officers using course-wide data and specialised software tools. These staff can access course-wide administrative data and also have skills to using specialised software, such as Turnitin’s “Authorship for Investigators”. Therefore, these officers can perform further analysis on student performance across their degree programmes and can apply policies and procedures consistently. Special software tools, and data in the databases with previous records or tools available at the Tertiary Education Quality and Standards Agency (TEQSA) website [35] could be used as the resources to analyse student records across the degree programme. TEQSA is an Australian national quality assurance and regulatory agency for higher education. More details on mitigation techniques, processes or tools that could be used by an AIO are discussed in Section 3.3.1.

According to the survey outcomes published in [36], 62.5% of students repeat contract cheating on multiple occasions. Hence, administrative data could also be useful in detecting unusual patterns between supervised and unsupervised assignments across the units in a degree programme [34]. A study conducted by Erguvan [37] showed that there was a lack of consistency in the measures adopted by academic staff to detect contract cheating at an institutional level. Therefore, there is a need for an AIO in the institute in order to maintain consistency in applying the policies.

2.3. Assignment Design

In this section, we briefly discuss how assignment design can be useful in identifying contract cheating. Bretag and Mahmud [31] explored the relationship between contract cheating and assessment design. There are no assessment tasks that can, in themselves, eradicate the apparent likelihood of contract cheating. However, proper assignment design would help assessors to detect instances of contract cheating. Educators need to consider evidence-based improvements in assessment design, teaching practices, and strategies to detect contract cheating.

An innovation in assessment design to mitigate contract cheating is more significant than applying a penalty after detection [34]. If contract cheating is not detected, a student would take risks again to repeat the behaviour in future assignments. Furthermore, students may seek external support for all kinds of assessments, including critical reflections, short turnaround time submissions, major assignments and even for supervised examinations [38,39]. Therefore, changing the assessment task every semester and considering factors influencing students to undertake good academic practices are other strategies to apply during assessment design [38].

Another possible way to detect contract cheating cases would be to use a variety of evaluation techniques in assignments. Different evaluation techniques, such as interviews/vivas, peer and self assessment and multiple-choice questions could be incorporated into assessment methods, which could positively influence the quality of assessment design. Assessment methods and assessment tasks could be the following: essays, peer assessment, portfolios, diary logs, group projects, and supervised examinations [3,40,41]. Different evaluation techniques on assessment design have been the subject of several research papers from a variety of perspectives and it is recommended that oral assessments, interviews, vivas, debates and recorded presentations are tasks that minimise opportunities for cheating [40,42]. Furthermore, some researchers emphasise the importance of self-assessment, especially in regard to formative assessments, where students check their own progress and evaluate their work against the assignment rubric [43]. Thus, students may become more self-regulated in their learning which, in turn, may contribute to enhanced honesty in their work [44,45].

3. Mitigate the Temptation to Cheat

Since contract cheating is on the rise, assessors and specialised staff might not be able to detect contract cheating in many cases. Therefore, prevention approaches to reduce contract cheating is a better and less expensive approach. Our literature review analysis and domain analysis demonstrate that contract cheating mitigation strategies can be viewed from three perspectives: student, staff, and administration.

3.1. Student Perspective

In this section, mitigation strategies from the students’ perspective are discussed. These strategies can be categorised into three areas: formal training, informal activities, and skill improvement.

3.1.1. Formal Training to Improve Awareness

Formal training and events play a central role in improving students’ awareness about academic integrity, including contract cheating. Formal compulsory training helps to discourage students by educating them about the negative consequences of contract cheating. It is important to conduct this formal academic integrity training early in the degree programmes for students to understand the potential marketing strategies used by contractors [2]. Currently, students receive academic integrity training during the orientation programme. Additionally, students are required to complete an Academic Integrity Module [46] during the first trimester of the course as a non-credit unit at the institute. Modules published by Oxford University press are available online for students and staff to develop internationally recognised best practices to avoid academic misconduct. In these modules students need to watch videos and complete quizzes.

3.1.2. Informal Activities

In addition to formal training and events, informal activities related to contract cheating and academic integrity are useful for international students. International students experience a lot of other difficulties during the transition period to their new study environment [47]. Hence, academic integrity awareness programmes conducted during orientation may not be effective for them. Conducting these awareness programmes again during the semester and placing posters to promote academic integrity in central locations may be helpful for them to understand the issue. For example, awareness activities, such as in class discussions, lunch time activities, and workshops conducted in the middle of the semester, could be implemented. Important topics for these discussions could include: consequences of contract cheating, the sternness of penalties, and instances of poor academic practices. Reminding students during lectures and laboratories may also reduce the chances of innocent students being exposed to advertisements published on cheating websites [48]. Furthermore, academics can closely work with students by organising research discussions, listening to videos, preparing research papers, and organising debates [49].

In addition to that, more workshops can be organised to enhance staff and students’ understanding of best academic practices. Furthermore, Epigeum Academic Integrity training, published by Oxford University Press [46], is available online for students and staff to develop internationally recognised best practices. These activities provide opportunities to staff (academics and administrators) to build their skills to use academic integrity resources consistently and effectively across all academic activities. Students who are aware of the issues and the penalties are more likely to comprehend the consequences of contract cheating and influence others to refrain from cheating. It is profitable to deliver these awareness sessions before submitting each assignment. These extra activities may help to minimise the risk of involvement in contract cheating.

3.1.3. Well-Equipped with Skills

One of the possible causes for contract cheating is students not being equipped with necessary skills to complete an assignment. Activities and support systems to strengthen student skills are critical to reduce the temptation for contract cheating. One promising strategy is to facilitate and inspire learners in developing the necessary academic skills and tools to complete their work [9,42,50]. These activities can be incorporated into laboratory classes prior to assignment due dates to enable students to strengthen skills to complete their assignments. Facilitation and inspiration may form a solid foundation for learning and, ultimately, reduce the risk of searching out dishonest ways to complete assignments.

It would also be beneficial to provide training to improve soft skills, such as time management, written and verbal communication skills, reading and learning skills, and study strategies. Suitable activities can be integrated into tutorials and problem-based learning classes. This limits the temptation to seek external assistance and also facilitates understanding the consequences of academic misconduct. Finally, students improve their confidence and skills to complete assignments successfully.

Furthermore, partially flipped classrooms or blended learning may create a setting to minimise cheating by building a student-centric learning environment. A study conducted in [51] found that multiple choice tests on Moodle, prior to a class, were a clear favourite in student activities. The students strongly agreed that pre-tests supported their learning and encouraged them to learn the materials outside the class. In this study, face-to-face class time was not reduced and the partially flipped approach inspired learners to learn outside class time for more active learning.

3.2. Staff Perspective

In this section, we discuss strategies from a staff perspective that can be applied to mitigate contract cheating. These strategies can be broadly focused on innovation in curriculum and assignment design, and applying techniques to identify contract cheating while marking assignments.

3.2.1. Innovation in Curriculum and Assessment Design

As discussed in Section 2.3, assignment design is an important tool to minimise opportunities for contract cheating. In addition to that, academics need to consider academic integrity at the curriculum development level and incorporate necessary measures to minimise opportunities across degree programmes [11,39,40].

3.2.2. Assignment Marking Strategies

Assignment marking strategies used by assessors play a crucial role in mitigating contract cheating. Most research has focused on academics’ perspectives of contract cheating. However, future research needs to be conducted from the students’ perspective of the issue. A few researchers have explored students’ reasons for contract cheating and one of the explanations was not receiving constructive, meaningful, and timely feedback from academics [52,53]. Students significantly improve their confidence level in understanding areas where they can improve by receiving constructive feedback [54]. A study conducted by Nicol indicated that feedback was effective if given as a dialogue process, rather than as a monologue [55].

In addition to providing feedback on the assignment, the marker also needs to focus on honest students’ genuine efforts to promote academic integrity. An important question associated with this problem is what measures can be taken to prevent cheaters gaining an unfair advantage. Although many studies have been conducted on contract cheating, this point is still insufficiently explored [2,39,40,56]. Markers can evaluate student assignments by monitoring their laboratory activities and progress on assignment preparation to prevent cheaters gaining an unfair advantage.

3.3. Administrative Approaches

TEQSA has highlighted the importance of administrative staff involvement in detecting and mitigating contract cheating cases [35,49,57]. TEQSA has published several resources and guidelines, highlighting key principles to follow to mitigate contract cheating [35,49,57]. These guidelines outline textual and technological signals to identify contract cheating, and include a brief guide on how to interview students, and warning signs that can be used by markers to detect suspected contract cheating [58]. The researchers in [59] conducted a review of academic integrity policies from 39 universities and proposed five core elements (access, approach, responsibility, detail, and support) that need to be considered when designing academic integrity policies. The proposed framework needs to consider various aspects of these guidelines and some can be addressed by introducing an AIO.

3.3.1. Academic Integrity Office (AIO)

Research has highlighted the importance of having an AIO and dedicated staff in the institution when considering an holistic approach to mitigate contract cheating [38,60,61]. Another suggestion is to provide necessary support for students who want to report to the tutor or to the University’s AIO if a student becomes aware that contract cheating has occurred [62]. This may be academic misconduct of a peer or evidence of contract cheating of a peer group. Many institutional academic misconduct policies do not entirely cover these aspects of the issue [15,63]. In this framework, we suggest introducing an integrity office and dedicated staff in the institution to ensure policies are consistently applied, existing policies and records are regularly evaluated and proper training is given to academic staff.

Research findings on academic misconduct bench-marking published by Scott et al. are available in [64]. These can be adopted by other institutions to define suitable and more consistent approaches when setting penalties, or as a tool for bench-marking internal regulations. For example, a benchmark plagiarism tariff or plagiarism reference tariff (iParadigms Europe) was developed in the UK through national research [64,65]. Furthermore, Harper and colleagues [40] surveyed students’ experiences and attitudes towards contract cheating and found three significant factors contributed to this issue: dissatisfaction with the teaching and learning environment, a perception that there were lots of opportunities to cheat’, and speaking a Language Other than English (LOTE) at home. They also indicated that it was beneficial to provide a well-recognised language learning center to support LOTE students, build strong student–teacher relationships to minimise opportunities for contract cheating and design curricula and assessments to minimise opportunities for contract cheating.

3.3.2. IP Tracking and Other Technical Ways to Identify Contract Cheating

IP tracking plays a crucial role in combating contract cheating as some contract cheating providers are operating internationally and existing laws are not designed to tackle international scenario. Therefore, the use of available technology is critical. Tracking IP addresses used to login to the LMS [35,62] and recording account access patterns are other possible approaches to identify international contract cheating service providers [66]. Some examples for unusual account access patterns are: using the same IP address to access different student accounts, accessing student accounts from different countries, and accessing student accounts during invigilated face-to-face on campus examination time. IP tracking may assist in detecting contract cheating, but detection is not a guarantee, as there are several other technical ways to avoid an IP address being captured. Some examples of technical ways to hide IP addresses are using virtual private networks and proxy servers.

Multiple-layer user validation is another possible approach to mitigate cheating in assignments. Ref. [67] discussed possible high-level student authentication options to minimise contract cheating, such as the following: bio-metric authentication, including scanning fingerprints or facial recognition; instructor validation (supervised study); student identity questions (online); using specialised software, such as proctoring software for remote monitoring.

3.3.3. Allow Some Room for Late Submissions with Reduced Penalty

The revision of current policy regarding late submission penalties may contribute to reducing the number of contract cheating cases. There are special consideration policies that allow late submissions without penalty. However, there is little understanding about these policies, especially regarding newly arrived international students, who may not be aware of them. Sometimes students may miss a few deadlines due to family and work commitments and allowing these students to submit assignments with a reduced penalty is better than their resorting to contract cheating.

4. An Holistic Framework to Detect and Mitigate Opportunities for Contract Cheating

The goal of this paper was to build an appropriate practical framework by using the findings from the domain analysis on contract cheating, policy document analysis at the institute as well as compiling self-efficacy theories [68,69]. As demonstrated in previous sections, recent research on contract cheating [2,3,6,38] highlighted the importance of having an holistic approach for addressing this issue. Furthermore, the research findings in [61,70] highlighted the inconsistencies in responding to contract cheating cases. Effective assessment design, and communicating and addressing potential issues as and when they occur are promising approaches to mitigating contract cheating [3]. In [8], the authors pointed out that markers’ suspicions may be crucial in addressing contract cheating. However, busy academics often rely only on Turnitin reports and are sometimes reluctant to make their own decisions to identify contract cheating, due to insufficient evidence or the amount of time they have to spend on investigations [38]. In [38], five important considerations, relevant to determining academic integrity, were proposed; reviewing the institutional policy, understanding students, re-visiting assessment practices and implications for staff professional development relating to academic integrity education. These strategies need to address priority areas first and to also emphasise the significance of other interrelated institutional activities, such as orientation, working with students, student feedback, staff induction and proper procedures to record student progress and concerns etc. Therefore, the institute needs to adopt an holistic approach to combat contract cheating.

A comprehensive institutional strategy can be brought to life by positioning a central AIO in the institution [38,71]. The central authority can develop a consistent and simpler process for detection and mitigation of contract cheating. Moreover, the institution’s academic misconduct policy should be visible to all stakeholders and should be connected to teaching, learning and assessment strategies. In order to evaluate the effectiveness of these strategies, the central authority may analyse patterns and trends of academic misconduct records and decide which subject areas and courses need to be improved or addressed.

This paper proposes a practical framework to formalise the response process and to generate a more consistent approach to detect or mitigate contract cheating [38,72]. The framework considers the institutional context of the issue after conducting a contract cheating domain analysis, policy analysis and also after applying self-efficacy theories. Figure 1 illustrates the process utilised to develop the proposed framework. In order to build an appropriate framework, first we conducted a contract cheating domain analysis and findings indicated that there were two strategies to combat contract cheating: detection and mitigation. Second, we performed a policy document analysis to understand the organisational structure and operating mechanisms of how contract cheating cases are handled in the institute. Then, we determined the gaps to be addressed in the proposed framework by collating findings between the literature review and policy analysis. Finally, we utilised self-efficacy theories to introduce PDT in the proposed framework.

4.1. Three-Tier Framework (TTF)

Figure 2 illustrates the proposed Three-Tier Framework (TTF), which is a first step towards compiling the wide range of factors that lessen the number of students involved in contract cheating and also provides an evidence-based strategy to identify contract cheating cases. We included section numbers of the paper in the description of the framework for better understanding of the key concepts discussed. The framework is divided into three levels. Level 1 i]focuses on Awareness, to increase understanding of contract cheating among students and staff before the beginning of a semester. Level 2 focuses on Monitoring, where the activities and tasks within this level are to be run during and after the semester. Level 3 focuses on Evaluation, to revise and improve existing institutional policies, procedures and services. Furthermore, three databases are introduced to operate this framework.

The three databases in the framework are:

1.

Monitoring database: a centralised shareable database updated by academics for recording assignment marks, the progress of assignment monitoring, assessor input, and suspected activities,

2.

Academic integrity breaches database: to record confirmed breaches by the AIO, and

3.

Software analysis reports: obtained from authorship investigations or similar software from LMS and uploaded by specialised administrative staff in the AIO.

4.1.1. Level 1—Awareness

The first tier of the framework explains the activities to be conducted before the semester starts. The awareness programmes need to be conducted during orientations, discussed in Section 3.1. The awareness programmes should consider the following areas to improve students’ overall awareness:

• Academic integrity including contract cheating
• Penalty associated with breaches
• Available student support services
• Support services available at Center of learning (CoL)
• Special consideration application process

In parallel to student awareness programmes, it is important to organise professional training for teaching staff which include inductions for new staff (Section 2.1):

• Inform new staff about contract cheating polices, procedures and services,
• Demonstrate trends, patterns and irregularities in potential cases with examples,
• Educate staff on assessment design, different evaluation techniques that can mitigate contract cheating cases, and
• Provide printed copies of institutional policies and a simple flow chart with the procedure they need to follow if they detect contract cheating.

This helps to improve shared understanding and consistent responses if contract cheating is detected. It can be achieved by developing compulsory training modules for staff to complete at their own paces, conducting workshops to provide an opportunity to share experiences from previous semesters and prompting the publication of high-profile research on contract cheating.

4.1.2. Level 2—Monitor

The second tier of the framework explains the activities to be conducted during the semester. Students have to complete two supervised and two unsupervised assignments, other than class participation, and contribution, as shown in

Table 1. A sample assessment table.

Assessment Task	Due Date	Supervised
Formative Assignment (FA)-(5%)	Week 3	No
In Class Test (ICT)-(10%)	Week 5–8	Yes
Assignment 2 (A2)-(25% to 30%)	Week 11	No
Class Participation and Contribution-(15%)	Weekly	No
Final Examination-(40–50%)	Week 13–14	Yes

, which is a snapshot of the assignments that need to be completed for a unit in a course. Contract cheating may happen in unsupervised assignments, such as Formative Assignment (FA) and Assignment 2 (A2), which are highlighted in Table 1. Each unit is coordinated by a unit coordinator and may have assigned tutors to conduct laboratory classes.

Before accusing students of contract cheating, tutors need to collect sufficient evidence to make correct judgments. The proposed framework uses PDT to monitor students’ work and collect more than one piece of evidence before accusing a student of cheating. A sample PDT is shown in

Table 2. A sample Pre-Designed Template (PDT).

Marks		Assessor Input		Progress—A2				Marks	Assessor Input
FA	ICT	OIS1	Comment	A2	A2	A2	Group	A2	OIS2	Comment

, which provides an opportunity to collect evidence. The unit coordinator would prepare the PDT for the unit and could add more fields if needed. These fields could be updated, based on common irregularities recorded in previous semesters. Next, we discuss how the fields of the PDT are completed during the unit delivery.

STEP  1:  Utilise  Formative  Assignment  (FA)  and  In  Class  Test  (ICT)  to  Observe  Irregularities  Stage  1  (OIS1)

As the first step in Level 2, tutors need to record student marks for FA and In Class Tests (ICTs) in PDT. After recording ICT marks, the marks of FA (unsupervised) and ICT (supervised) are compared, and irregularities identified, as discussed in Section 2.2.2. The observation is recorded in a column called “Observed Irregularities Stage 1 (OIS1)” in PDT with “Y” or “N” and with comments and uploaded on to “Monitoring Database”.

STEP  2:  Discourage  the  Temptation

Step 2 plays a key role in discouraging the temptation to engage in contract cheating in major unsupervised assignment A2. A few possible steps to discourage temptation to cheat can be conducted before the A2 due date. Such activities could be:

• Ensuring that students are well equipped with the necessary skills and understand the assessment (Section 3.1).
• Allocating the last 30 min of laboratory classes to discussing A2 requirements until the due date.
• Recording student progress on A2 in PDT three times, as discussed in the next Step, and informing the student of this activity. This helps tutors to compare student performance and make students aware of the monitoring progress used for detection of contract cheating.
• Discussing the special consideration application process and other student support services available.
• Allowing late submission up to a specified number of days past the due date with a reduced penalty (Section 3.3.3).

In addition to the above activities, academics may consider other additional activities to discourage the temptation to cheat. Some key tasks that can be performed by academics are:

• Preparing suitable assessment design by incorporating vivas, interviews or presentations for assignment evaluations (Section 2.3 and Section 3.2.2).
• Organising extra informal activities (Section 3.1) during the trimester, such as class discussions, lunch time activities, workshops, competitions, debates, research discussions, video presentations with real examples of penalties,
• Conducting sessions to enhance soft and hard skills to ensure students have the ability to do the assignment. (Section 3.1).
• Incorporating blended learning activities, such as pre-class quizzes, recorded lectures, and extra videos relevant to the topics to improve student confidence and, eventually, enhance enthusiasm for learning.

STEP  3:  Monitor  Assignment  2  (A2)  Progress  and  assign  numeric  grades  to  Categorise:

In this step, the tutors observe A2 progress three times (for example, weeks six (6), eight (8) and 10) and record in PDT. To record the progress, the tutors can

• Observe A2 progress and enter a numeric grade in the scale of one (1) (lowest) to 10 (highest) to record student’s progress on A2 (Section 2.2.2) three times. The numeric grade is recorded in PDT depending on assignment progress shown during the monitoring process.
• Calculate three-week average obtained by each student. The progress demonstration is considered successful if a student obtains five (5) or above as three-week average, otherwise it is considered unsuccessful.
• Categorise students into two groups: Group A and Group B. Tutors make an academic judgment and assign students to either Group A or Group B based on the following rule:
      Group A  = Successful demonstration of A2 progress(three-week
                average > 5) AND
                 no irregularities observed in OIS1 AND
                 good class participation
   
      Group B  = Unsuccessful demonstration in class (three-week
                  average <= 5) OR irregularities observed in OIS1
                 OR poor class participation
• The group of each student is recorded in PDT under the column “Group” before marking A2.

STEP 4: Evaluate A2:

Before evaluating A2, the tutor carefully observes grouping information and other comments available in PDT (Table 2) stored in the monitoring database. Tutors mark A2 by providing proper feedback and focusing on honest students’ genuine efforts (Section 3.2.2). If they feel uncertain whether the written work was done by a student or not, they conduct a viva. Finally, tutors upload the marks and document irregularities in OIS2 column in PDT with comments. When tutors upload these observations on to a central shareable database online, a particular student’s behaviour can be observed for all units by the Academic Integrity Officer and this speeds up the investigations on contract cheating in Step 6 and Step 7.

STEP 5: Evaluate Final Examination and Class Participation and Contribution:

Tutors assess final examination papers, class participation and contribution reports carefully by observing the information available in Table 2 and store their findings in the last comment column of the monitoring database. Any observed irregularities and suspected contract cheating cases found during these evaluations are directly reported to the AIO.

STEP 6: Perform Data Analysis on Unit Level:

At this stage data analysis at the unit level is conducted by the unit coordinator after observing recorded data in the PDT in the shareable database called, “Monitoring Database” and identified cases are escalated to the AIO. If the group categorisation in STEP 3 is not matching, tutors or unit coordinators can still confirm their observations by conducting an interview with the student. These interview results can be used to deal with suspected contract cheating fairly and consistently by updating the comments in the PDT.

STEP 7: Perform Data Analysis on Course Level:

At this stage data analysis on course level is conducted by the Academic Integrity Officer. This analysis is initiated by the AIO. The data analysis considers the data in three databases (monitoring database from all units; Academic integrity breach database; and data from authorship investigation) and any other inputs from academics. Additionally, the AIO performs further investigation on the cases reported by academic staff (including unit coordinators and tutors) by using these three databases. Unit coordinators report a summary of observations or recommendations specific to contract cheating from unit delivery to the AIO. The information can be be used in staff professional training and staff meetings.

STEP 8: Penalty Decision

The AIO decides on and applies the penalty, according to the policy, after analysing the data from three (3) databases. The monitoring database is a centralised database and contains course level data and assessors’ reports. The academic integrity breach database is also a centralised database and contains previous academic breaches with detailed reports. The third database is a report generated by software tools. Finally, the AIO updates the “Academic integrity breach database” if there are records with academic integrity breaches. This process ensures that there is a consistent approach to handle contract cheating.

4.1.3. Level 3—Evaluation

At this level, an overall evaluation and revision of the institutional policies, procedures and services related to contract cheating is conducted. Firstly, the data analysis reports generated using the three databases are presented to relevant committees. These committees utilise the report findings and industry trends to update the institutional policies and procedures related to contract cheating. Secondly, formal and informal surveys among staff are used to evaluate their understanding and the effectiveness of policies, procedures and services related to contract cheating. These survey findings are utilised to enhance the quality of staff professional training (Level 1). Additionally, staff opinions and perceptions are provided to the relevant committees as inputs for updating the institutional policies and procedures related to contract cheating. Finally, students’ perception on overall activities related to contract cheating is evaluated using a student survey. This survey should be integrated with existing student surveys. These survey findings are used to revise student activities in Step 2 (Level 2) and are also used to revise and update student orientation and awareness programmes (Level 1) to enhance their effectiveness. The overall findings from the student survey also need to be reported to the relevant committees. These actions ensure that the institutional policies, procedures, and services are up-to-date in order to handle recent changes and current trends in contract cheating.

5. Conclusions, Limitations and Future Works

In this section, we present concluding remarks of this work, key limitations of the proposed framework, and possible future works on the framework.

5.1. Conclusions

Contract cheating is a growing problem in the higher education industry, which may lead to creation of unskilled and unqualified graduates entering the workforce. To address this problem, this paper introduced a conceptual framework to minimise contract cheating. The proposed framework was based on research findings on contract cheating domain analysis, policy analysis, and self-efficacy theories. The domain analysis indicated that the solution to this complex problem is two fold: finding appropriate approaches to detect contract cheating and developing strategies to mitigate opportunities for contract cheating. The policy analysis highlighted the gaps in existing institutional policies and procedures. These analyses were bundled up with self-efficacy theories to yield an holistic framework to combat contract cheating at the institute level.

The proposed framework has three-tiers: Awareness, Monitoring, and Evaluation. Student awareness and staff professional skills on contract cheating are enhanced at the awareness level using various activities. Students’ activities associated with assignments are recorded using PDT and monitoring possible contract cheating cases by conducting data analysis using three databases at the monitoring level. The possible contract cheating cases are evaluated by an AIO using data analysis at the course level. Institutional policies, procedures and services related to contract cheating are evaluated and revised at the evaluation level on a regular basis using feedback mechanisms. Therefore, the proposed framework establishes an holistic approach to combat contract cheating at the course level, applies institutional policies consistently through an AIO and provides evidence to support detecting of cheated cases.

5.2. Limitations

This was an initial step towards developing a practical framework to mitigate and detect contract cheating but the framework alone is not able to solve the whole contract cheating problem. Next, we need to evaluate the framework after receiving feedback from all stakeholders. If this framework is adopted by other institutes, it should be customised to the institutional context. The proposed framework did not consider several factors, including ethical issues, teaching delivery methods and discipline specific issues. Students and staff ethical concerns are not considered in the proposed framework. We acknowledge the fact that some stages of the framework may not be appropriate or not applicable to courses in different disciplines with different modes of delivery.

5.3. Future Works

Ongoing research is needed to test the framework in practice. An action research approach using self-efficacy theories will be helpful in the future to improve this framework. After consultation with the relevant authorities at the institute, this framework will be tested and validated by conducting suitable research. We anticipate that this research will serve as an additional support for developing more consistent and holistic approaches in future research on contract cheating.