AI Use in Assessments: Your role in protecting the integrity of qualifications

Executive Summary

While the potential for student artificial intelligence (AI) misuse is relatively new, most of the ways to prevent misuse and mitigate the associated risks are not; centres will already have established measures in place to ensure students are aware of the importance of submitting their own independent work for assessment and for identifying potential malpractice. 

This document highlights the regulations that apply in relation to AI use in assessments and provides guidance to help teachers and assessors in centres. 

This document emphasises the following requirements: 

• In accordance with 5.3(k) of the JCQ General Regulations for Approved Centres, teachers and assessors must only accept work for qualification assessments which is the students’ own; 
• Students who misuse AI to the extent that the work they submit for assessment is not their own will have committed malpractice in accordance with JCQ regulations and could attract severe sanctions; 
• Students and centre staff must be aware of the risks of using AI and must be clear on what constitutes malpractice; 
• Students must ensure work submitted for assessment is demonstrably their own. If any sections of their work are reproduced directly from AI-generated responses, those elements must be identified by the student and they must understand this will not allow them to demonstrate they have independently met the marking criteria and therefore will not be rewarded (please see the Acknowledging AI use and AI use and marking sections below and Appendix B: Exemplification of AI use in marking student work at the end of this document); and 
• Where teachers have doubts about the authenticity of student work submitted for assessment (for example, they suspect that parts of it have been generated by AI but this has not been acknowledged), they must investigate and take appropriate action. 

The JCQ awarding organisations’ staff, examiners and moderators have established procedures for identifying, reporting and investigating student malpractice, including the misuse of AI. 

This document refers to AI tools and AI detection tools as they were at the time of publication; the JCQ awarding organisations are continuing to monitor developments in this area and will update this document when appropriate. 

Examples of candidate AI misuse cases and marking candidate work where AI tools have been used can be found in appendices A and B to this document. 

Additional support materials, aimed at teachers and students, can be found here: 

JCQ-AI-poster-for-students-2.pdf 
JCQ-AI-information-sheet-for-teachers-1.pdf 

Updating the JCQ guidance on AI Use in Assessments – JCQ Joint Council for Qualifications – this will take you to links for two presentations – one for SLT to use with teachers and one for teachers to use with students

Key changes since last version 

Section	Paragraph	Summary of change
Front cover	Document title	Added that this is for the attention of Heads of Centre, as well as teachers and assessors
Executive summary	Final paragraph	Added links to the additional support materials available on the JCQ website
1. The assessments the regulations and guidance apply to	First paragraph	Added that care must be taken around use of laptops in exams, to ensure AI tools cannot be accessed
2. What is AI use and what are the risks of using it in assessments?	Bulleted lists setting out examples of AI tools	Added additional tools, including those that can generate video content
3. What is AI misuse by students?	Second paragraph	Added links to other JCQ documents where student requirements are set out
4. Centre responsibilities	First section	Added reference to the responsibilities on Heads of Centre that are set out in the General Regulations as well as reference to other relevant regulations
4. Centre responsibilities	Lettered list of what centres must do	One bullet removed, two new ones added
7. Preventing AI misuse in assessments	Third paragraph	Added information around the mechanisms schools must have in place
Appendix A: AI misuse examples	Examples 5 and 6	Added two further examples from malpractice cases
Appendix C: Extracts from JCQ regulations and guidance relevant to use of AI	Full appendix	New appendix drawing together information from different published documents which is relevant to AI

1. The assessments the regulations and guidance apply to 

2. What is AI use and what are the risks of using it in assessments? 

3. What is AI misuse by students? 

4. Centre responsibilities

5. Acknowledging AI use 

6. AI use and marking 

7. Preventing AI misuse in assessments 

While there may be benefits to using AI in some situations, there is the potential for it to be misused by students, either accidentally or intentionally. AI misuse, in that it involves a student submitting work for qualification assessments which is not their own, can be considered a form of plagiarism. JCQ has published guidance on plagiarism in assessments, which covers what it is, how to prevent it, and how to detect it. 

Teachers and assessors must be assured that the work they accept for assessment and mark is the student’s own work. They are required to confirm this during the assessment process and, if they have doubts, must follow their centre’s internal procedures and published guidance for assessment. 

Centres must have mechanisms in place, as previously referenced in the section titled ‘Centre Responsibilities’, which include: 

• the approach the centre will use to prevent and identify AI misuse in each of the subjects including coursework or non-examined assessment that it delivers, including the approach taken for any private candidates. 
• the process to follow where there are concerns about AI misuse before the student’s work is authenticated. In this situation, the centre is responsible for determining next steps and a teacher/assessor should not refer the work to the awarding organisation for a decision. 

Those who work with the students on a regular basis and are familiar with their ability and standard of work are usually best-placed to make determinations about the misuse of AI although the relevant awarding organisation is available to provide advice and guidance to help the centre where needed. 

To prevent misuse, education and awareness of staff and students is likely to be key. Here are some actions which could be taken (many of these will already be in place in centres as these are not new requirements): 

a) Consider restricting access to online AI tools on centre devices and networks; 

b) Ensure access to online AI tools is restricted on centre devices used for exams; 

c) Set reasonable deadlines for submission of work and providing reminders; 

d) Where appropriate, allocate time for sufficient portions of work to be completed in class under direct supervision to allow the teacher to authenticate all of each student’s work with confidence; 

e) Examine intermediate stages in the production of work in order to ensure work is underway in a planned and timely manner and work submitted represents a natural continuation of earlier stages; 

f) Introduce classroom activities that use the level of knowledge/understanding achieved during the course thereby making the teacher confident the student understands the material; 

g) Consider whether it is helpful to engage students in a short verbal discussion about their work to ascertain they understand it and it reflects their own independent work; 

h) Do not accept, without further investigation, work which staff suspect has been taken from AI tools without proper acknowledgement or is otherwise plagiarised – doing so encourages the spread of this practice and is likely to constitute staff malpractice which can attract sanctions. 

i) Issuing tasks for centre-devised assignments which are, wherever possible, topical, current and specific, and require the creation of content which is less likely to be accessible to AI models trained using historic data.

8. Identifying misuse in assessments 

Identifying the misuse of AI by students requires the same skills and observation techniques teachers are already using to assure themselves student work is authentically their own. There are also some tools that may be used. These different methods are explored below. 

Comparison with previous work 

When reviewing a given piece of work to ensure its authenticity, it is useful to compare it against other work created by the student. Teachers could consider comparing newly submitted work with work completed by the student in the classroom, or under supervised conditions. Where the work is made up of writing, it is possible to make note of the following characteristics: 

• Spelling and punctuation 
• Grammatical usage 
• Writing style and tone
• Vocabulary 
• Complexity and coherency 
• General understanding and working level 
• The mode of production (i.e. whether handwritten or word-processed) 

Private candidates 

Verifying the authenticity of work submitted by private candidates can be more challenging for centres, given they may not have a good understanding of the standard the student is currently working at. Before accepting entries from a private candidate for a subject that includes NEA or coursework, the centre must consider the steps they will take that will enable the teachers/assessors to ensure the work submitted for assessment is the student’s own independent work. This may involve requiring the student to undertake some of the work under supervision, a review of the student’s portfolio of evidence across a range of qualifications and a short discussion with the student regarding their work. 

• Further guidance on authenticating student work can be found in the JCQ Instructions for conducting coursework. 

Potential indicators of AI misuse 

If the following are seen in student work, it may be an indication the student has misused AI: 

a) A default use of American spelling, currency, terms and other localisations. 

b) A default use of language or vocabulary which may not accord with the qualification level (though be aware AI tools may be instructed to employ different languages, registers and levels of proficiency when generating content). 

c) A lack of direct quotations and/or use of references where these are required/ expected (though some AI tools will produce quotations and references). 

d) Inclusion of references which cannot be found or verified (some AI tools have provided false references to books or articles by real authors). 

e) A lack of reference to events occurring after a certain date (reflecting when an AI tool’s data source was compiled), which may be notable for some subjects.

f) Instances of incorrect and/or inconsistent use of first-person and third-person perspective where generated text is left unaltered. 

g) A difference in the language style used when compared to that used by a student in the classroom or in other previously submitted work. 

h) A variation in the style of language evidenced in a piece of work, if a student has taken significant portions of text from AI and then amended it. 

i) A lack of graphs/data tables/visual aids where these would normally be expected. 

j) A lack of specific local or topical knowledge. 

k) Content being more generic in nature rather than relating to the student themself, or a specialised task or scenario, if this is required or expected. 

l) The inadvertent inclusion by students of warnings or provisos produced by AI to highlight the limits of its ability, or the hypothetical nature of its output. 

m) The submission of student work in a typed format, where their normal output is handwritten. 

n) The unusual use of several concluding statements throughout the text, or several repetitions of an overarching essay structure within a single lengthy essay, which can be a result of AI being asked to produce an essay several times to add depth and variety or to overcome its output limit. 

o) The inclusion of strongly stated non-sequiturs or confidently incorrect statements within otherwise cohesive content. 

p) Overly verbose or hyperbolic language that may not be in keeping with the candidate’s usual style. 

Automated detection 

AI tools, as large language models, produce content by ‘guessing’ the most likely next word in a sequence. This means AI-generated content uses the most common combinations of words, unlike humans who tend to use a variety of words in their normal writing. Several programs and services use this difference to statistically analyse written content and determine the likelihood that it was produced by AI, for example: 

• Copyleaks (https://copyleaks.com/ai-content-detector) 
• GPTZero (https://gptzero.me/) 
• Sapling (https://sapling.ai/ai-content-detector) 
• Turnitin AI writing detection (https://www.turnitin.com/solutions/topics/ai-writing/ai-detector/) 

These may be used as a check on student work and/or to verify concerns about the authenticity of student work. However, it should be noted that the above tools will give lower scores for AI-generated content which has been subsequently amended by students, as they base their scores on the predictability of words. Spending time getting to know how the detection tools work will help teachers and assessors understand what they are and are not capable of. 

AI detection tools, including those listed above, employ a range of detection models which vary in accuracy depending on the AI tool and version used, the proportion of AI to human content, prompt types and other factors (such as an individual’s English language competency). In instances where misuse of AI is suspected it may be helpful to use more than one detection tool to provide an additional source of evidence about the authenticity of student work. 

The use of detection tools, where used, should form part of a holistic approach to considering the authenticity of students’ work; all available information must be considered when reviewing any malpractice concerns. Teachers will know their students best and so are best placed to assess the authenticity of work submitted to them for assessment – AI detection tools can be a useful part of the evidence they can consider.

The list of certain suppliers of AI-related products is for information purposes only and does not constitute an endorsement by JCQ. It is each centre’s responsibility to investigate and verify any suppliers they use, including any terms and conditions which govern the sale or use of the supplier’s products. The list provided is not exhaustive.

9. Reporting 

If a student has not signed the declaration of authentication, centres do not have to report the incident to the appropriate awarding organisation. Steps to resolve such incidents must be detailed in the centre malpractice/plagiarism policy. These steps must include: 

• ensuring students are aware of what malpractice is, 
• how to avoid malpractice, 
• how to properly reference sources and acknowledge AI tools, etc. 

Teachers must not accept work which is not the student’s own. Ultimately the Head of Centre has the responsibility for ensuring students submit authentic work. 

If AI misuse is detected or suspected by the centre and the declaration of authentication has been signed by the student, the case must be reported to the relevant awarding organisation. The procedure is detailed in the JCQ Suspected Malpractice: Policies and Procedures.

10. Awarding Organisation actions 

The JCQ awarding organisations ensure staff, moderators and examiners are appropriately trained in the identification of malpractice and have established procedures for reporting and investigating suspected malpractice. 

If AI misuse is raised by or reported to an awarding organisation, full details of the allegation will usually be relayed to the centre. The relevant awarding organisation will liaise with the Head of Centre regarding the next steps of the investigation and how appropriate evidence will be obtained. The awarding organisation will then consider the case and, if necessary, impose a sanction in line with the sanctions given in the JCQ Suspected Malpractice: Policies and Procedures (https://www.jcq.org.uk/exams-office/malpractice/). The sanctions applied to a student committing plagiarism and making a false declaration of authenticity range from a warning regarding future conduct to disqualification and the student being barred from entering for one or more examinations for a set period of time. 

Examples of AI misuse cases dealt with by awarding organisations may be found in Appendix A: AI misuse examples at the end of this document. 

Awarding organisations will also take action, which can include the imposition of sanctions, where centre staff are knowingly accepting, or failing to check, inauthentic work for qualification assessments.

Appendix A: AI misuse examples 

Introduction 

The following are anonymised examples from recent malpractice cases involving the misuse of AI tools. Please note although specific subjects are identified in the examples below, the circumstances described, and the associated actions and sanctions could be applied to any qualification. The following have been chosen so as to give examples which cover a range of different contexts, including where centres have reported AI misuse concerns and where awarding body assessment personnel have identified potential issues. The fourth example is an example of what can go wrong when word processors have not been correctly set up for examinations. 

Plagiarism – AI misuse 

Awarding body: AQA
Qualification: A Level History NEA 

A centre reported one of its teachers for A Level History had concerns relating to two candidates’ NEA submissions. The concerns were that multiple sections were inconsistent with other parts of the candidates’ work and the candidates’ usual levels and styles of writing. 

The centre used AI detection software to follow up on the teacher’s concerns. The centre’s review identified the following. 

Candidate A: The AI detection software identified the work as being highly likely to have been generated by AI. This candidate admitted using ChatGPT to generate a guideline for their own work and claimed that they had accidentally submitted the guideline instead of their own work. 

Candidate B: The AI detection software identified the work as being potentially generated by AI, and likely a combination of AI and human input. This candidate admitted using ChatGPT for some of the content of their work, for both the improvement of their own work as well as the creation of entirely new content. 

The centre reported both candidates to the awarding body and provided confirmation that the candidates had been issued all relevant ‘information for candidates’ documents and the candidates had signed the declaration of authenticity to declare that the work completed was their own. 

Both candidates were found to have committed malpractice. Candidate A was disqualified from the A Level History qualification and Candidate B received a loss of all marks gained for the A Level History NEA component. 

Awarding body: OCR
Qualification: Cambridge Nationals Enterprise and Marketing 

The moderator raised concerns of suspected plagiarism in a unit of the above qualification, due to a lack of referencing seen within candidates’ work. 

Through using Turnitin, two candidates were identified who may have potentially used AI tools, or Large Language Models (LLMs), to generate content for at least one Learning Objective. These included explanations of different business terms and financial analyses. 

One candidate admitted to using ChatGPT in the later parts of their coursework as they had not understood some of the questions and felt assistance from their teacher was “too infrequent”. They stated their logic was it was no different to asking a teacher for advice as the AI tool would take information from across the internet and since they were asking specific questions, the ‘reply’ from the AI tool would be the same as getting teacher advice and feedback.

The other candidate admitted they had used an AI tool to generate content for their work but couldn’t remember which sections of work had been their own. 

Although the cohort had been told about plagiarism and how to avoid it, there had been no specific mention of AI tools – despite AI misuse being a form of plagiarism. 

Based on the evidence provided by the centre, it was determined that the two candidates would receive zero marks for the affected Learning Objectives. 

Awarding body: Pearson
Qualification: Extended Project P301 

During a regular review of work for the purposes of identifying potential AI misuse, a candidate’s Extended Project submission was identified by detection software as containing several unreferenced sections of AI generated content. A further evaluation of the submission concluded multiple sections of the work included extensive indicators associated with generative AI. Upon contacting the centre, the candidate declined to provide a statement explaining the concerns, and the case was referred to Pearson’s Malpractice Committee for consideration. 

Following a careful review of the available evidence, the Malpractice Committee found the candidate to be in breach of the JCQ AI Use in Assessments document which defines as malpractice “copying or paraphrasing sections of AI-generated content so that the work submitted for assessment is no longer the student’s own” and “failing to acknowledge use of AI tools when they have been used as a source of information”. 

The Malpractice Committee determined, as the result of the malpractice, the candidate be disqualified from the qualification. 

Awarding body: AQA
Qualification: GCSE Religious Studies 

A candidate’s word processed exam script was reported to the malpractice team by the examiner marking it because they had identified frequent American spellings and they felt the highly sophisticated language and concepts it contained were not consistent with GCSE level work. 

The candidate’s word processed script was reviewed using AI detection software which returned a high probability score for the use of AI. The candidate was asked to provide a statement, in which they denied the use of AI. 

After consideration of the evidence gathered, it was decided the candidate had breached examination conditions and used AI for the production of answers in their examination. The candidate received a loss of all marks gained for a component. 

Post-results, it was also concluded by the centre the candidate’s marks and grades were not consistent with expectation or previous attainment. Following the outcome of this case and the disparity in performance flagged by the centre, all of the candidate’s assessments were processed through AI detection software which showed multiple components were affected. The outcome was that the candidate received a loss of all marks gained for the affected components. 

Following an investigation it was found that the candidate’s word processor had not been correctly set up. Internet access should have been disabled for the word processor, which would have prevented this malpractice from occurring. As part of the investigation, the awarding body sought to ensure that such incidents could not recur. The centre gave details of the steps that would be taken to prevent a recurrence of this issue, which included the re-training of invigilators on word processor set up.

Awarding body: OCR
Qualification: A Level Art and Design 

A candidate was suspected of having AI-generated content from DeepL, an AI-powered translation tool, in their sketchbook for A Level Art and Design. The Deputy Head of the centre explained that the candidate’s approach involved researching in their own language and then translating all of this into English. The candidate admitted they used DeepL to translate source material into their sketchbook and were aware that this was not allowed for their assessment. By translating their work in this way, the candidate effectively called into question the overall authenticity of the work. From that point onward, it became unclear what ideas, knowledge, and understanding presented were entirely their own. 

The teacher reported that while reviewing the candidate’s work, they identified several sections with writing inconsistencies. Through their own internal analysis, the centre estimated 98% of the content to be influenced by AI. The candidate explained that most of their academic materials were in their own language, which caused difficulties in their work. They assumed that DeepL would be a reliable and accurate translator for their needs. However, they were unaware that it utilised AI support. Despite checking DeepL’s website, they did not realise the seriousness of using AI at the time and would have avoided translation software had they known. The centre stated that candidates were made fully aware of the rules and regulations around AI use leading up to the assessment. 

The JCQ Instructions for Conducting Non-Examination Assessments prohibit candidates from using the internet or other sources without acknowledgment. It is evident that the candidate breached the assessment regulations by not acknowledging and referencing the use of an AI-powered translation tool in their work. Furthermore, the candidate was aware of the implications as the centre had, on multiple occasions, provided guidance on referencing and AI. Additionally, the candidate signed a declaration of authenticity form confirming that the work submitted was their own, which included that they had clearly referenced any sources and AI tools they had used. In view of the above and in accordance with the JCQ Suspected Malpractice Policies and Procedures document, the candidate was sanctioned with a loss of marks which resulted in zero marks being awarded for the component. 

Awarding body: WJEC
Qualification: Level 3 Diploma in Criminology, Unit 3 controlled assessment 

During a centre’s internal moderation process and prior to work being submitted to WJEC moderation, an assessor/teacher at the centre suspected that part of the work presented was not entirely the candidate’s own. 

It was suspected by the assessor that certain assessment criteria within the work did not match the work produced within other assessment criteria produced by the candidate. 

With this particular qualification, candidates are permitted to take a folder of general notes into the assessment based on prior research for an unseen assignment brief. 

When comparing the assessment criteria of concern to the notes the candidate took into the assessment, it was found that the candidate had copied their notes word for word, and they were identified as being generated by AI. The candidate had not referenced the source as AI-generated and had not declared it. 

On receipt of the candidate’s work WJEC conducted further checks of the work via an AI detection tool, which provided evidence to confirm the centre’s suspicion. 

The checks of the candidate’s full body of work did not detect any further AI-generated content elsewhere. 

As part of the investigation, the candidate confirmed that they had used an AI tool for one section of their notes only, due to rushing to prepare their notes prior to the assessment taking place.

Following a careful review of the available evidence, WJEC determined that the candidate was in breach of the assessment requirements and JCQ AI Use in Assessments document which defines as malpractice “copying or paraphrasing sections of AI-generated content so that the work submitted for assessment is no longer the student’s own” and “failing to acknowledge use of AI tools when they have been used as a source of information”. 

WJEC decided that as a result of the AI misuse being confined to one assessment criteria, the candidate received a penalty of loss of marks for a section. The impact of which resulted in the candidate not obtaining the overall qualification, as all assessment criteria for the unit must be met and a minimum number of marks must be achieved in each assessment criteria to gain the qualification.

Appendix B: Exemplification of AI use in marking student work 

Introduction 

The following are examples of how the JCQ AI Use in Assessments document relating to students using AI tools can be applied by teachers and assessors when students have not independently met the marking criteria, as per page 8 of this document: “b) Students are also reminded if they use AI they have not independently met the marking criteria therefore they will not be rewarded.” In the below examples, students have not independently met the marking criteria because of their over reliance on AI tools. 

Examples 

Awarding body: Pearson
Qualification: A Level History 

A candidate has produced coursework for the NEA component of the qualification which is of a good standard. The candidate has used a range of sources and AI tools which have been appropriately cited within the work. The candidate has demonstrated some understanding of the topic, using generally correct and appropriate information. The candidate has also expressed an opinion on the topic at hand and has attempted some discussion of differing viewpoints. The work is clear and coherent but does lack depth. 

The assessor marking the work at the centre consults the mark scheme for this component and identifies that the work is likely to attract marks which make it fall within Level 3. The mark scheme for this level is as follows: 

Level	Mark	Descriptor
Level 3 17-24		Explains analysis and attempts evaluation A range of material relevant to the enquiry has been identified from reading and appropriately cited. Information has been appropriately selected and deployed to show understanding of the overall issue in question. A judgement on the question is related to some key points of view encountered in reading and discussion is attempted, albeit with limited substantiation. Contextual knowledge of some issues related to the debate is shown and linked to some of the points discussed. Analyses some of the views in three chosen works by selecting and explaining some key points and indicating differences. Explanation demonstrates some understanding of the reasons for differences. Attempts are made to establish valid criteria for evaluation of some arguments in the chosen works and to relate the overall judgement to them, although with weak substantiation. Mostly accurate and relevant knowledge is included to demonstrate some understanding of the conceptual focus of the enquiry, but material lacks range or depth. The answer is concise and shows some organisation. The general trend of the argument is clear, but parts of it lack logic, coherence and precision.
	Low level 3: 17-18 marks  The qualities of Level 3 are displayed, but material is less convincing in some aspects and it is not concise.	Mid level 3: 19-21 marks  The qualities of Level 3 are displayed, but material is less convincing in some aspects or it is not concise.	High level 3: 22-24 marks  The qualities of Level 3 are securely displayed.

Having carefully considered the descriptors and the candidate’s work, the assessor considers the work is of a high level 3 standard, worth 22-24 marks. However, for the section in the work in which the candidate discusses some key points and differences between three historical resources, the candidate has relied solely upon an AI tool. This use has been appropriately acknowledged and a copy of the input to and output from the AI tool has been submitted with the work. As the candidate has not independently met the marking criteria they cannot be rewarded for this aspect of the descriptor (i.e. the third bullet point above). The assessor therefore places the work in the mid-level 3 category, awarding 20 marks. 

The assessor ensures this decision regarding the student’s AI use and its impact on marking is clearly recorded. This provides feedback to the student and provides clarity in the event of an internal appeal or the work being selected for moderation. 

Awarding body: Pearson Qualification: BTEC Level 3 National Extended Diploma in Business 

A student has produced work for unit 1: Exploring Business. The student has produced work of a good standard in which they have compared two different businesses in some depth. The candidate has used a range of sources and AI tools which have been appropriately cited within the work. In the work the student has assessed the relationship with stakeholders of the two companies, analysed the two organisations’ structures, discussed the effects of the business environment on the companies – including their response to recent and potential future changes in the market, and reviewed the importance of innovation and entrepreneurship in the success of one of the companies. 

The assessor carefully reviews the assessment criteria for unit 1, which are as follows: 

Assessment Criteria

Pass	Merit	Distinction
Learning aim A: Explore the features of different businesses and analyse what makes them successful
A.P1 Explain the features of two contrasting businesses. A.P2 Explain how two contrasting businesses are influenced by stakeholders.	A.M1 Assess the relationship and communication with stakeholders of two contrasting businesses using independent research.	AB.D1 Evaluate the reasons for the success of two contrasting businesses, reflecting on evidence gathered.
Learning aim B: Investigate how businesses are organised
B.P3 Explore the organisation structures, aims and objectives of two contrasting businesses.	B.M2 Analyse how the structures of two contrasting businesses allow each to achieve its aims and objectives.
Learning aim C: Examine the environment in which businesses operate
C.P4 Discuss the effect of internal, external and competitive environment on a given business. C.P5 Select a variety of techniques to undertake a situational analysis of a given business.	C.M3 Assess the effects of the business environment on a given business.	C.D2 Evaluate the extent to which the business environment affects a given business, using a variety of situational analysis techniques.
Learning aim D: Examine business markets
D.P6 Explore how the market structure and influences on supply and demand affect the pricing and output decisions for a given business.	D.M4 Assess how a given business has responded to changes in the market.	C.D3 Evaluate how changes in the market have impacted on a given business and how this business may react to future changes.
Learning aim E: Investigate the role and contribution of innovation and enterprise to business success
E.P7 Explore how innovation and enterprise contribute to the success of a business.	E.M5 Analyse how successful the use of innovation and enterprise has been for a given business.	E.D4 Justify the use of innovation and enterprise for a business in relation to its changing market and environment.

The assessor is content that the work meets all Pass, Merit and Distinction criteria. However, the assessor is aware that in the section in which the student discusses how one of the businesses might react to future changes in the business environment, the student has relied upon the use of an AI tool (appropriately acknowledged, with the input and output from the AI tool submitted together with the assignment) and has not independently demonstrated their own understanding beyond this. The assessor therefore cannot award criterion D.D3 and, as the work has not met all Distinction assessment criteria (which is required to achieve an overall Distinction grade), the work is awarded a Merit grade overall. 

The assessor ensures this decision regarding the student’s AI use and its impact on marking is clearly recorded. This provides feedback to the student and provides clarity in the event of an internal appeal or the work being selected for standards verification.

Appendix C: Extracts from JCQ regulations and guidance relevant to the use of AI 

This appendix draws together into one place information from different JCQ documents which is relevant to preventing AI misuse, for ease of reference. You do not need to read the full appendix and nor does it represent any new information; the aim is to help you easily access applicable information in the extracts below. These explain the responsibilities of centre staff and candidates, which are relevant to managing the use of AI. 

Note that these are extracts only and do not reflect the full guidance and regulations, which can be accessed via the following links: 

General Regulations for Approved Centres 
Instructions for Conducting Examinations 
Instructions for Conducting Coursework 
Instructions for Conducting Non-Examination Assessments (GCE & GCSE Specifications) 

General Regulations for Approved Centres

Section	Content	Who is it for
5.3k	It is the responsibility of the Head of Centre to ensure that their centre: has in place arrangements to co-ordinate and standardise all marking of centre-assessed components and to ensure that candidates’ centre-assessed work is produced, authenticated and marked, or assessed and quality assured in accordance with the awarding bodies’ instructions. This applies to both internal and private candidates.	Centre staff
5.3z	It is the responsibility of the Head of Centre to ensure that their centre: has in place the following policies for inspection that must be reviewed and updated annually: • a written malpractice policy which covers all qualifications delivered by the centre. The policy must detail how candidates are informed and advised to avoid committing malpractice in examinations/assessments, how suspected malpractice issues should be escalated within the centre and reported to the relevant awarding body. It must also acknowledge the use of AI (e.g. what AI is, when it may be used and how it should be acknowledged, the risks of using AI, what AI misuse is and how this will be treated as malpractice). • a written policy regarding the management of non-examination assessments including controlled assessments and coursework. (For CCEA GCSE centres this would be a written controlled assessments policy.)	Centre staff
5.11	The centre will: e) conduct all examinations/assessments governed by these regulations in accordance with the following JCQ documents for the academic year 2024/25:  Access Arrangements and Reasonable Adjustments, Instructions for conducting coursework, Instructions for conducting examinations, Instructions for conducting non-examination assessments	Centre staf

Instructions for Conducting Examinations

Section	Content	Who is it for
14.25	A word processor: f. must be used to produce work under secure conditions, otherwise the candidate’s script may not be accepted; g. must not be used to perform skills which are being assessed; h. must not give the candidate access to other applications such as a calculator (where prohibited in the examination), email, the internet, social media sites, spreadsheets; j. must not have any predictive text software or an automatic spelling and grammar check enabled unless the candidate has been permitted a scribe (a scribe cover sheet must be completed), or the awarding body’s specification permits the use of automatic spell checking;	Centre staff

Instructions for Conducting Coursework

Section	Content	Who is it for
3.1	All coursework submitted for assessment must be the candidate’s own work	Candidate
5.1	In many subjects, candidates will use source material, including the internet and AI, when carrying out their coursework. However, candidates must not copy such material and claim it as their own work.	Candidate
5.2	If candidates use material from a source or generated from a source which is not their own work, they must indicate the particular part/element/phrase and state where it came from. Candidates must give detailed references even when they paraphrase the original material. Where computer-generated content has been used (such as an AI Chatbot), the reference must show the name of the AI bot used and should show the date the content was generated. For example: ChatGPT 3.5 (https://openai.com/blog/chatgpt/). 25/01/2025. Candidates should retain a copy of the computed-generated content for reference and authentication purposes.	Candidate
6.1	Candidates must not: • submit work which is not their own; • use AI, books, the internet or other sources without acknowledgement   or attribution; • misuse AI;	Candidate
6.2	If irregularities in coursework are discovered prior to the candidate signing the declaration of authentication, this should be dealt with under the centre’s internal procedures and does not need to be reported to the awarding body. Details of any work which is not the candidate’s own must be recorded on the authentication form supplied by the awarding body or other appropriate place.	Candidate
6.3	If irregularities in coursework are identified by a centre after the candidate has signed the declaration of authentication, the Head of Centre must submit full details of the case to the relevant awarding body immediately.	Candidate
6.7	Heads of centre and appropriate senior leaders must ensure that those members of teaching staff involved in the direct supervision of candidates producing coursework are aware of the potential for malpractice.	Candidate
7.1	Each candidate (candidate being defined as someone for whom an entry is in place for the unit or qualification) must sign a declaration when submitting their coursework to their teacher for final assessment. Electronic signatures are acceptable. This is to confirm that the work is their own and that any assistance given and/or sources used have been acknowledged. Ensuring that they do so is the responsibility of the centre. Centres must record marks of ‘0’ (zero) if candidates cannot confirm the authenticity of work submitted for assessment.	Candidate
7.2	Teachers must confirm that all of the work submitted for assessment was completed under the required conditions and that they are satisfied the work is solely that of the individual candidate concerned. If they are unable to do so, the work must not be accepted for assessment.  All teachers must sign the declaration of authentication after the work has been completed. Electronic signatures are acceptable. Failure to sign the authentication statement may delay the processing of the candidate’s results.  If, during the external moderation process, it is found that the work has not been properly authenticated, the awarding body will set the mark(s) awarded by the centre to ‘0’ (zero).	Candidate
7.3	The teacher should be sufficiently aware of the candidate’s standard and level of work to be able to identify if the coursework submitted appears to be beyond that candidate’s talents.	Candidate
7.4	In most centres, teachers are familiar with candidates’ work through class and homework assignments. Where this is not the case, teachers should require coursework to be completed under direct supervision.	Candidate
7.5	In all cases, some direct supervision is necessary to ensure that the coursework submitted can be confidently authenticated as the candidate’s own.	Candidate
7.6	If teachers have reservations about signing the authentication statements, the following points of guidance should be followed:  • if it is believed that a candidate has received additional assistance and this is acceptable within the guidelines for the relevant specification, the teacher should award a mark which represents the candidate’s unaided achievement. The authentication statement must be signed and information given on the relevant form;  • if the teacher is unable to sign the authentication statement of a particular candidate, then the candidate’s work cannot be accepted for assessment. A mark of ‘0’ (zero) must be submitted;  • if malpractice is suspected, a member of the senior leadership team must be consulted about the procedure to be followed.	Candidate
8.1	When marking coursework, teachers must pay close attention to the requirements of the specification. Teachers should note that it is their responsibility to award marks for coursework in accordance with the marking criteria detailed in the awarding body’s specification and subject-specific associated documents. Teachers must show clearly how the marks have been awarded in relation to these marking criteria. The centre’s marks must reflect the relative attainment of all the candidates.  Teachers must not use artificial intelligence as the sole means of marking candidates’ work	Candidate

Appendix 2 – Information for candidates – coursework assessments effective from 1 September 2024

You can demonstrate your knowledge and understanding of a subject by using information from sources or generated from sources which may include the internet and AI. Remember, though, information from these sources may be incorrect or biased. You must take care how you use this material – you cannot copy it and claim it as your own work.  The regulations state that: ‘the work which you submit for assessment must be your own’; Where computer-generated content has been used (such as an AI Chatbot), your reference must show the name of the AI bot used and should show the date the content was generated. For example: ChatGPT 3.5 (https://openai.com/blog/chatgpt/), 25/01/2025. You must submit a copy of the computer-generated content with your work for reference and authentication purposes. Don’t be tempted to use any pre-prepared or generated online solutions and try to pass them off as your own work – this is cheating. Electronic tools used by awarding bodies can detect this sort of copying. Plagiarism involves taking someone else’s words, thoughts, ideas or outputs and trying to pass them off as your own. It is a form of cheating which is taken very seriously.

Candidate

Instructions for Conducting Non-Examination Assessments (GCE & GCSE Specifications)

Section	Content	Who is it for
	How do the awarding bodies monitor the management of non-examination assessments in centres?  Awarding bodies require each centre to have a non-examination assessment policy in place to:  • to cover procedures for planning and managing non-examination assessments;  • to define staff roles and responsibilities for non-examination assessments;  • to manage risks associated with non-examination assessments.	Centre staff

Instructions for Conducting Non-Examination Assessments (GCE & GCSE Specifications)

Section	Content	Who is it for
4.1 Supervision	Where appropriate to the component being assessed, the following arrangements apply unless the awarding body’s specification says otherwise. Candidates do not need to be directly supervised at all times. The use of resources, including the internet, is not tightly prescribed. Centres must always check the subject-specific requirements issued by the awarding body. The centre must ensure that: • there is sufficient supervision of every candidate to enable work to   be authenticated; • the work that an individual candidate submits for assessment is their own. Work may be completed outside of the centre without direct supervision, provided that the centre is confident that the work produced is the candidate’s own. Centres must ensure that candidates understand what they need to do to comply with the regulations for non-examination assessments. This is outlined in the JCQ document Information for candidates – non-examination assessments. Centres must ensure that candidates: • understand that information from all sources must be referenced; • receive guidance on setting out references; • are aware that they must not plagiarise other material.	Centre staff
4.3 Resources	What resources are allowed? In many subjects, candidates will use source material, including the internet and AI, when researching and planning their tasks. Candidates normally have unrestricted access to resources. Centres must refer to the JCQ document AI Use in Assessments: Protecting the Integrity of Qualifications, as well as the awarding body’s specification and/or associated documentation published by the awarding bodies and the regulator. Some subjects require candidates to produce the work for assessment in formally supervised sessions. Unless the awarding body’s specification says otherwise, for all formally supervised sessions: • the use of resources is always tightly prescribed and normally restricted to the candidate’s preparatory notes;  • access to the internet is not permitted;  • candidates are not allowed to use their own computers or other electronic devices, e.g. mobile phones. Are candidates allowed to introduce new resources in-between formally supervised sessions?  No. Candidates are not allowed to augment notes and resources between sessions. When work for assessment is produced over several sessions, the following material must be collected and stored securely at the end of each session (and not be accessible to candidates):  • the work to be assessed;  • preparatory work.  Additional precautions need to be taken if the centre permits candidates to use computers to store work. This may involve collecting memory sticks for secure storage between sessions or restricting candidates’ access to a specific area of the centre’s IT network. How should sources be acknowledged?  The work submitted for assessment must include references where appropriate. To facilitate this, each candidate should keep a detailed record of their own research, planning, resources etc. The record should include all the sources used, including books, websites and audio/visual resources.  Guidance is given in the JCQ document Information for candidates – non-examination assessments	Candidate and centre staff
4.6 Authentication procedures	How is candidates’ work authenticated? Teachers must be sufficiently familiar with the candidate’s general standard to judge whether the piece of work submitted is within his/her capabilities.  Where required by the awarding body’s specification, the following procedures apply.  All candidates must sign a declaration to confirm that the work they submit for final assessment is their own unaided work.  Teachers must sign a declaration of authentication after the work has been completed confirming that:  • the work is solely that of the candidate concerned;  • the work was completed under the required conditions.  Electronic signatures are acceptable. Typed names will be taken as being as binding as a handwritten signature. What if the teacher has doubts about the authenticity of the work?  If teachers are unable to confirm that the work presented by a candidate is their own and has been completed under the required conditions:  • do not accept the candidate’s work for assessment;  • record a mark of ‘0’ (zero) for internally assessed work.  If teachers are concerned that malpractice may have occurred or are unable to authenticate the work for any other reason, they must inform a member of the senior leadership team (see section 9).  If, during the external moderation process, it is found that the work has not been properly authenticated, the awarding body will set the mark(s) awarded by the centre to ‘0’ (zero).	Centre staff and candidate
6.1 Marking and annotation	Teachers are responsible for marking work in accordance with the marking criteria detailed in the relevant specification and associated subject-specific documents.  Teachers must not use artificial intelligence as the sole means of marking candidates’ work.	Centre staff
9 Malpractice	Candidates must not:  • submit work which is not their own;  • make available their work to other candidates through any medium;  • allow other candidates to have access to their own independently sourced material;  • assist other candidates to produce work; • use books, the internet or other sources without acknowledgement or attribution; • submit work that has been word processed by a third party without acknowledgement;  • include inappropriate, offensive or obscene material. Teaching staff must:  • be vigilant in relation to candidate malpractice and be fully aware of the published regulations;  • escalate and report any alleged, suspected or actual incidents of malpractice to the senior leadership team or directly to the awarding body.	Candidate and centre staff

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