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The Language of Assessment: Identifying Challenging Terminology for Students and Exploring Implications for Practice

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Title: The Language of Assessment: Identifying Challenging Terminology for Students and Exploring Implications for Practice
Language: English
Authors: Harry West (ORCID 0000-0002-2704-5474), Nicole Skidmore, Laura Bennett, Juliet Eve, Cathy Minett-Smith, Luke Rudge
Source: Assessment & Evaluation in Higher Education. 2025 50(3):381-395.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 15
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Vocabulary, Evaluation, Feedback (Response), Foreign Countries, College Students, Documentation, Language Usage, Self Esteem
Geographic Terms: United Kingdom (England)
DOI: 10.1080/02602938.2024.2402960
ISSN: 0260-2938
1469-297X
Abstract: Many interventions have been developed by staff to support students in understanding assessment task requirements and summative and formative feedback. However, to various extents, these approaches assume a shared understanding of the, often indeterminate, language used in assessment. This article reports on a project, which aimed to explore students' confidence in interpreting frequently used language in assessment and feedback documentation and explore ways in which staff can work with students to address misunderstanding and misinterpretation. To do this, we undertook a corpus-based linguistic analysis of assessment documentation to identify frequently used and potentially problematic language. We then used a survey and focus groups to explore with students their confidence in interpreting these terms. In doing so, we identify commonly used assessment and feedback terminology, which students find challenging to interpret, potentially resulting in frustration and demotivation. We conclude by exploring different approaches reported by students in the focus groups which help them interpret challenging terminology, notably different forms of dialogic-based intervention, but note, however, that time and space are needed within the curriculum for a shared (or ideally co-created) understanding of language to be developed between students and staff.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1484579
Database: ERIC
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  Value: <anid>AN0184922429;eva01may.25;2025May06.04:47;v2.2.500</anid> <title id="AN0184922429-1">The language of assessment: identifying challenging terminology for students and exploring implications for practice </title> <p>Many interventions have been developed by staff to support students in understanding assessment task requirements and summative and formative feedback. However, to various extents, these approaches assume a shared understanding of the, often indeterminate, language used in assessment. This article reports on a project, which aimed to explore students' confidence in interpreting frequently used language in assessment and feedback documentation and explore ways in which staff can work with students to address misunderstanding and misinterpretation. To do this, we undertook a corpus-based linguistic analysis of assessment documentation to identify frequently used and potentially problematic language. We then used a survey and focus groups to explore with students their confidence in interpreting these terms. In doing so, we identify commonly used assessment and feedback terminology, which students find challenging to interpret, potentially resulting in frustration and demotivation. We conclude by exploring different approaches reported by students in the focus groups which help them interpret challenging terminology, notably different forms of dialogic-based intervention, but note, however, that time and space are needed within the curriculum for a shared (or ideally co-created) understanding of language to be developed between students and staff.</p> <p>Keywords: Assessment terminology; language; feedback; dialogue</p> <hd id="AN0184922429-2">Introduction</hd> <p>Universities frequently receive relatively low student satisfaction scores for assessment (Yang and Carless [<reflink idref="bib56" id="ref1">56</reflink>]; MacKay et al. [<reflink idref="bib32" id="ref2">32</reflink>]) and perceptions of inconsistency are a cause of concern for students (Bloxham et al. [<reflink idref="bib8" id="ref3">8</reflink>]). However, a truly standardised assessment system is unlikely, not least due to the often indeterminate nature of many terms used in Higher Education contexts (Morrish and Sauntson [<reflink idref="bib39" id="ref4">39</reflink>]). There have been efforts to reduce inconsistency, such as the development of standards-based assessment through publication of marking criteria which are generic and student focused (Alonzo et al. [<reflink idref="bib3" id="ref5">3</reflink>]) and social calibration amongst staff to highlight differences and form a common consensus of standards (Wyse et al. [<reflink idref="bib55" id="ref6">55</reflink>]).</p> <p>Many practices have been proposed to help students interpret assessment documentation, including supporting students to self-evaluate (Nicol and Kushwah [<reflink idref="bib42" id="ref7">42</reflink>]; Gladovic et al. [<reflink idref="bib18" id="ref8">18</reflink>]) and generate internal feedback (Nicol [<reflink idref="bib41" id="ref9">41</reflink>]), developing glossaries of assessment terminology (Richards and Pilcher [<reflink idref="bib45" id="ref10">45</reflink>]), using exemplars (Bell et al. [<reflink idref="bib6" id="ref11">6</reflink>]; Worth [<reflink idref="bib54" id="ref12">54</reflink>]), adopting dialogic feedback (Hill and West [<reflink idref="bib23" id="ref13">23</reflink>], [<reflink idref="bib24" id="ref14">24</reflink>]), or through co-creation of marking criteria (Orsmond et al. [<reflink idref="bib44" id="ref15">44</reflink>]; Meer and Chapman [<reflink idref="bib37" id="ref16">37</reflink>]) and other forms of student-staff partnership (Matthews et al. [<reflink idref="bib34" id="ref17">34</reflink>]). When students meaningfully engage with and reflect upon assessment documentation, performance is improved, and the benefits of assessment/feedback literacy are realised. Carless ([<reflink idref="bib14" id="ref18">14</reflink>]) proposed this as new paradigm of feedback that prioritised active student roles in feedback as a dialogic process. Winstone and Carless ([<reflink idref="bib52" id="ref19">52</reflink>]) expand on this and highlight three student-focussed elements: sense-making, learner generation of inputs and emphasis on student action. However, many of these practices assume a common understanding of the language used in assessment and feedback. This is critical to the success of many of these interventions, especially those involving dialogue (Matthews et al. [<reflink idref="bib35" id="ref20">35</reflink>]).</p> <p>Research has identified that students' confidence in interpreting assessment and feedback language can vary. There are elements of criteria and standards which are socially constructed, and interpretation will differ between individuals and groups (Ajjawi and Bearman [<reflink idref="bib2" id="ref21">2</reflink>]). There are terms and phrases used which students struggle to interpret, such as 'synthesise, 'analyse', 'evaluate' and 'discuss' (O'Donovan et al. [<reflink idref="bib43" id="ref22">43</reflink>]; Richards and Pilcher [<reflink idref="bib45" id="ref23">45</reflink>]). Boyle et al. ([<reflink idref="bib10" id="ref24">10</reflink>]) also identify that language inferring the quality of a piece of work, such as 'good' or 'better', can be difficult for students to distinguish between, given inherently subjective or context-dependent interpretations. Challenges also arise where familiar terminology is used in unfamiliar assessment-related contexts, for example 'meeting' learning outcomes (Butcher et al. [<reflink idref="bib13" id="ref25">13</reflink>]).</p> <p>O'Donovan et al. (2004) distinguish between explicit and tacit knowledge in interpreting assessment and feedback terminology. Students find it challenging to decode tacit assessment requirements (Boyle et al. [<reflink idref="bib10" id="ref26">10</reflink>]) such as 'developing an argument' (Butcher et al. [<reflink idref="bib13" id="ref27">13</reflink>]), using 'the literature' (Matshedisho [<reflink idref="bib33" id="ref28">33</reflink>]), or being 'critical' (Richards and Pilcher [<reflink idref="bib45" id="ref29">45</reflink>]). Similar statements which often require such tacit understanding are used in feedback such as 'too descriptive', 'superficial analysis' or 'fails to answer the question' (Adcroft [<reflink idref="bib1" id="ref30">1</reflink>]), contributing to the common misalignment between the message from the feedback provider and receiver (Jones and Ellison [<reflink idref="bib27" id="ref31">27</reflink>]).</p> <p>Different demographic groups of students are more likely to be experience challenges with the language of assessment as interpretation takes place through cultural and linguistic lenses (Rossiter [<reflink idref="bib46" id="ref32">46</reflink>]). A lack of clarity in assessment criteria has a disproportionate effect on already disadvantaged groups of students (Balloo et al. [<reflink idref="bib5" id="ref33">5</reflink>]), such as widening participation students (Butcher et al. [<reflink idref="bib13" id="ref34">13</reflink>]). Gonsalves ([<reflink idref="bib19" id="ref35">19</reflink>]) found that international students (for whom English may be not their first language) can struggle with interpretation of assessment rubrics and that consideration is needed in how criteria are presented and used within task to enhance accessibility.</p> <p>Whilst there are practices that help to minimise inconsistencies, intuitive and tacit variability is unavoidable (Yorke [<reflink idref="bib57" id="ref36">57</reflink>]; Bloxham et al. [<reflink idref="bib8" id="ref37">8</reflink>]). It is, therefore, important that staff develop an understanding of which frequently used language students struggle to understand, potentially limiting their engagement with assessment tasks, inhibiting their development of assessment literacy, and undermining their agency as learners (Lee et al. [<reflink idref="bib30" id="ref38">30</reflink>]). Understanding which student groups are likely to experience challenges in interpreting assessment terminology due to social and cultural differences (Rossiter [<reflink idref="bib46" id="ref39">46</reflink>]) is also timely to address awarding gaps. Being aware of the potentially ambiguous language of assessment and developing strategies within our teaching to acknowledge and address it underpin the development of inclusive learning environments, which enable students to succeed.</p> <hd id="AN0184922429-3">Study context</hd> <p>This article reflects on work undertaken over the 2020–2021 and 2021–2022 academic years to investigate students' confidence in interpreting assessment and feedback language and to identify ways in which staff can work with students to reduce feelings of uncertainty and clarify meaning. This work forms part of a wider QAA (Quality Assurance Agency) Collaborative Enhancement Project. The project was undertaken across four teaching-oriented universities based in central and southern England. This research was approved by all four institutional research ethics committees. The project team was comprised of staff representatives (including academic staff developers, professional services, and academics) and student partners.</p> <p>The present study is split into three stages, which combined represent a mixed-methods analysis of assessment terminology and associated student understanding. Stage 1 utilised corpus linguistic analysis to identify common assessment language from a range of documentation. This informed Stages 2 and 3 which explored students' confidence in interpreting the identified terminology, and ways staff can minimise confusion and misinterpretation through a survey and focus groups. The overall aim was to identify problematic terminology used in assessment so that staff can reflect on when and where certain terminology is used in the assessment process and support students to clarify meaning and enhance assessment/feedback literacy.</p> <hd id="AN0184922429-4">Methods</hd> <p></p> <hd id="AN0184922429-5">Stage 1: linguistic analysis of assessment documentation</hd> <p>The project aim was to determine the extent to which there is a variation in students' confidence in interpretation of language used in assessment documentation. However, this could only be completed in a robust manner by initially following sound linguistic methodology to identify common instances of language use. Each institution performed equivalent corpus analyses of their analogous assessment documentation, with the goal being to apply corpus-based linguistic methodologies to query the language used (McEnery and Hardie [<reflink idref="bib36" id="ref40">36</reflink>]). This provided insight into identifying common terms and phrases relating to assessment, marking and regulation, and the level of performance. Each institution complied documentation from across seventeen subject areas, mapped to the UK HECoS CAH1 codes (the Common Aggregation Hierarchy codes provide a standardised approach to grouping subjects/disciplines across the higher education sector in the UK).</p> <p>The documentation was compiled and analysed using Sketch Engine (Kilgarriff et al. [<reflink idref="bib28" id="ref41">28</reflink>]), made available via the EU Horizon 2020-funded ELEXIS project. Each institution complied one main corpus (a total of four across the project), and each also consisted of four subcorpora: 1) assessment briefs, 2) learning outcomes, 3) marking criteria and grade descriptors, and 4) assessment policy documentation. The smallest of the four institutional corpora was 84,224 words and the largest 646,776 words. The combined corpora totalled 1,390,676 words.</p> <p>First, a word frequency analysis of common parts of speech (i.e. nouns, verbs, adjectives, and adverbs) was undertaken to identify recurring vocabulary. Word frequencies were normalised by corpus length to ensure comparability across corpora. Second, keyword analysis identified statistically salient single and multi-word terms relative to a corpus of everyday British English usage: the English Web 2020 corpus. Manual confirmation was employed to remove false positives and to investigate how the identified vocabulary is used in context via collocational analysis.</p> <p>The results were then compared to identify lexical patterns, discrepancies and the terminology that would feed into Stage 2. The top 100 words/phrases from each institution were compiled and duplicates were removed. The project team systematically went through this list, first individually and then collaboratively to define a list which was categorised into 'assessment language' that provides instruction to students (e.g. define, analyse, explain), 'feedback language' which would be used in formative or summative feedback to students (e.g. superficial analysis, descriptive writing, relevance), and 'quality descriptors' (e.g. good, excellent, poor). Examples of concordance (Gablasova et al. [<reflink idref="bib17" id="ref42">17</reflink>]) were also extracted and can be found in Supplementary Materials for this article.</p> <hd id="AN0184922429-6">Stage 2: student survey and focus groups</hd> <p>Stage 2 of this research sought to explore students' confidence in interpreting the assessment language identified in Stage 1. First, an online survey was launched across the four institutions; distributed via institutional academic development units and professional services departments to undergraduate module/unit leaders who were asked to promote the survey to students. Prior to participating, students were given an overview of the project and asked to provide informed consent.</p> <p>Student respondents were presented with Likert scale questions asking them to indicate on a scale of 1–6 their confidence in interpreting the word or phrase (where 1 was not at all confident in interpretation, and 6 was certain in understanding). Demographic information was also recorded (Table S1).</p> <p>In total, there were 318 survey responses across the four institutions. Most respondents were below the age of 24, did not report a disability, stated English as their first language and reported their ethnicity as white. However, there was a greater range of respondents by year of study, with a relatively even split across FHEQ Levels 4–6 (Years 1–3 of full-time undergraduate study in England).</p> <p>The Likert-scale responses were analysed, with the words and phrases ranked according to the average confidence score across the four-partner institutions. Additionally, we compared the responses between different demographic groups using Kruskal–Wallis statistical tests for the word groups individually, and for a combined set of responses.</p> <hd id="AN0184922429-7">Stage 3: Focus groups and thematic analysis</hd> <p>Focus groups and one-to-one interviews with 31 students were conducted using Microsoft Teams and were recorded and transcribed using automatic transcription software. Reflexive thematic analysis (Braun and Clarke [<reflink idref="bib11" id="ref43">11</reflink>], [<reflink idref="bib12" id="ref44">12</reflink>]) was used to analyse the transcripts and identify themes, with the aim of capturing patterns in participants' accounts and identifying areas in which language used in assessment was confusing, unclear, or unhelpful, or where the opposite was true. Codes were clustered together at each institution, and these were later shared with an additional team member so that they could determine whether patterns were evident across the dataset. Finally, representatives from each institution discussed the final themes in detail and ensured that each theme cohered around a central organizing concept, which is the key idea that underpins thematic explanation of data (Terry et al. [<reflink idref="bib50" id="ref45">50</reflink>]), and that theme names captured these concepts. To keep participants in the focus groups anonymous, quotations in this paper will not report any identifiable information. To aid readability and comprehension, verbal nods (e.g. pauses and repeated words) have been removed from the data: '[...]' indicates omitted data.</p> <hd id="AN0184922429-8">Results</hd> <p></p> <hd id="AN0184922429-9">Stage 1: linguistic analysis of assessment documentation</hd> <p>Initially, we identified the level of overlap in the terms used in the assessment documentation. The top 100 nouns, verbs, adjectives, and adverbs were extracted from each institutions corpus and duplicates removed. On average there were 173 individual terms and phrases from a potential total of 400 (100 per institution), representing a 43.4% overlap in assessment terminology across the four institutions. A total of 54 individual terms/phrases were selected to take forward. These terms had a high frequency of use across the institutional corpora and were categorised as 'assessment language', 'feedback language' or 'quality descriptors'. The results from this analysis and examples of concordance can be found in the Supplemental Material.</p> <hd id="AN0184922429-10">Stage 2: student survey results</hd> <p>This section presents survey results where respondents were asked to rate their confidence in interpreting the terminology identified in Stage 1. The average interpretation score and variance are presented for each institution and from the combined set of results.</p> <p>Figure 1 shows the average interpretation score and variance for the 'assessment' focused language. Several terms received low interpretation scores such as 'critical' and 'examine'. In particular, the term 'synthesise' received very low scores. These terms also had high variance indicating there is greater variability in students' ability to interpret these terms when completing an assessment task. Conversely language such as 'explain' and 'summarise' had higher average scores and lower variance indicating that these are terms students interpret with greater confidence.</p> <p>PHOTO (COLOR): Figure 1. Average student interpretation score and variance for assessment-related terminology. Terms are listed in ascending order based on the overall average value across the four institutions.</p> <p>PHOTO (COLOR): Figure 2. As per Figure 1, however, for feedback-related terms.</p> <p>Figure 2 presents the interpretations scores and variance for the feedback terms. The terminology which received lower scores and high variance include 'superficial analysis' and 'abstract'. Other low-scoring terms include 'reflective' and 'application of theory'. These also had high variance suggesting greater variability in students' confidence in understanding this language when used in feedback. Conversely, terms/phrases with higher confidence and lower variance (i.e. where students consistently feel confident in their understanding) include 'successfully', 'fails to answer the question' and 'relevance'.</p> <p>Across the three terminology groups, the quality descriptors had higher levels of student confidence in interpretation (Figure 3). The quality descriptors with higher levels of confidence and lower variance include 'excellent' and the adverb 'extremely'. The descriptor 'competent' had the lowest average score and highest average variance.</p> <p>PHOTO (COLOR): Figure 3. As per Figure 1, however, for quality descriptors. NB no data were recorded for the term adequate for university 2 (U2).</p> <p>Table 1 presents the statistical comparison between demographic groups based on all terms in the survey. Significant differences were found between demographic categories for age, disability, ethnicity, and level of study. Students below the age of 20, reported a learning disability, reported their ethnicity as Asian or were in Level 4 or 5, statistically gave lower confidence scores in their ability to interpret the terminology. Students who were older, did not have a disability, were white/black or in their final (Level 6) year of study, reported higher confidence.</p> <p>Table 1. Kruskal–Wallis test results for all words/phases in the survey. PNS abbreviates 'prefer not to say' responses.</p> <p> <ephtml> <table><thead><tr><td /><td>Age</td><td>Disability</td><td>First Language</td><td>Ethnicity</td><td>Level</td></tr><tr><td>Significance (<italic>p</italic> value)</td><td char=".">0</td><td char=".">0</td><td char=".">0.513</td><td char=".">0</td><td char=".">0</td></tr></thead><tbody valign="top"><tr><td>Groups (<italic>z</italic> scores)</td><td><20</td><td char=".">−8.67</td><td>Yes</td><td char=".">−8.68</td><td>Yes</td><td char=".">−0.78</td><td>Asian</td><td char=".">−7.96</td><td>L4</td><td char=".">−7.18</td></tr><tr><td>21–24</td><td char=".">4.74</td><td>No</td><td char=".">7.42</td><td>No</td><td char=".">0.93</td><td>Black</td><td char=".">5.02</td><td>L5</td><td char=".">−10.09</td></tr><tr><td>25–29</td><td char=".">5.54</td><td>PNS</td><td char=".">0.14</td><td>PNS</td><td char=".">−0.73</td><td>Mixed</td><td char=".">0.38</td><td>L6</td><td char=".">17.94</td></tr><tr><td>30+</td><td char=".">3.81</td><td /><td /><td /><td /><td>Other</td><td char=".">4.16</td><td /><td /></tr><tr><td>PNS</td><td char=".">−4.82</td><td /><td /><td /><td /><td>PNS</td><td char=".">−4.42</td><td /><td /></tr><tr><td /><td /><td /><td /><td /><td /><td>White</td><td char=".">2.23</td><td /><td /></tr></tbody></table> </ephtml> </p> <p>Table 2 presents the comparative analysis between demographic groups for the assessment-related terms in the survey. Significant differences were found for all demographic groups in line with the above description for Table 1, with the addition of those who report English as being their first language as having lower confidence in interpreting the assessment terminology.</p> <p>Table 2. Kruskal–Wallis Test results for assessment-related terms. PNS abbreviates 'prefer not to say' responses.</p> <p> <ephtml> <table><thead><tr><td /><td>Age</td><td>Disability</td><td>First language</td><td>Ethnicity</td><td>Level</td></tr><tr><td>Significance (<italic>p</italic> value)</td><td char=".">0</td><td char=".">0</td><td char=".">0.024</td><td char=".">0</td><td char=".">0</td></tr></thead><tbody valign="top"><tr><td>Groups (<italic>z</italic> scores)</td><td><20</td><td char=".">−5.82</td><td>Yes</td><td char=".">−10.35</td><td>Yes</td><td char=".">−2.72</td><td>Asian</td><td char=".">−1.88</td><td>L4</td><td char=".">−2.49</td></tr><tr><td>21–24</td><td char=".">1.68</td><td>No</td><td char=".">8.33</td><td>No</td><td char=".">2.7</td><td>Black</td><td char=".">5.49</td><td>L5</td><td char=".">−8.72</td></tr><tr><td>25–29</td><td char=".">3.9</td><td>PNS</td><td char=".">1.05</td><td>PNS</td><td char=".">0.22</td><td>Mixed</td><td char=".">−0.13</td><td>L6</td><td char=".">11.59</td></tr><tr><td>30+</td><td char=".">3.94</td><td /><td /><td /><td /><td>Other</td><td char=".">1.91</td><td /><td /></tr><tr><td>PNS</td><td char=".">−1.99</td><td /><td /><td /><td /><td>PNS</td><td char=".">−0.97</td><td /><td /></tr><tr><td /><td /><td /><td /><td /><td /><td>White</td><td char=".">−2.17</td><td /><td /></tr></tbody></table> </ephtml> </p> <p>Tables 3 and 4 show the statistical test results for the feedback and quality terminology. Similar demographic patterns as previously described are present; however, first language groups show no significant differences, and learning disability groups also show no significant difference for the quality descriptor group.</p> <p>Table 3. Kruskal–Wallis Test results for feedback-related terms. PNS abbreviates 'prefer not to say' responses.</p> <p> <ephtml> <table><thead><tr><td /><td>Age</td><td>Disability</td><td>First language</td><td>Ethnicity</td><td>Level</td></tr><tr><td>Significance (<italic>p</italic> value)</td><td char=".">0</td><td char=".">0.004</td><td char=".">0.781</td><td char=".">0</td><td char=".">0</td></tr></thead><tbody valign="top"><tr><td>Groups (<italic>z</italic> scores)</td><td><20</td><td char=".">−7.01</td><td>Yes</td><td char=".">−2.9</td><td>Yes</td><td char=".">0.4</td><td>Asian</td><td char=".">−5.03</td><td>L4</td><td char=".">−7.05</td></tr><tr><td>21–24</td><td char=".">4.81</td><td>No</td><td char=".">3.31</td><td>No</td><td char=".">−0.28</td><td>Black</td><td char=".">2.32</td><td>L5</td><td char=".">−4.67</td></tr><tr><td>25–29</td><td char=".">3.58</td><td>PNS</td><td char=".">−1.42</td><td>PNS</td><td char=".">−0.63</td><td>Mixed</td><td char=".">−0.33</td><td>L6</td><td char=".">12.23</td></tr><tr><td>30+</td><td char=".">2.52</td><td /><td /><td /><td /><td>Other</td><td char=".">2.42</td><td /><td /></tr><tr><td>PNS</td><td char=".">−4.18</td><td /><td /><td /><td /><td>PNS</td><td char=".">−3.96</td><td /><td /></tr><tr><td /><td /><td /><td /><td /><td /><td>White</td><td char=".">2.51</td><td /><td /></tr></tbody></table> </ephtml> </p> <p>Table 4. Kruskal–Wallis Test results for quality descriptors. PNS abbreviates 'prefer not to say' respondents.</p> <p> <ephtml> <table><thead><tr><td /><td>Age</td><td>Disability</td><td>First language</td><td>Ethnicity</td><td>Level</td></tr><tr><td>Significance (<italic>p</italic> value)</td><td char=".">0.015</td><td char=".">0.301</td><td char=".">0.171</td><td char=".">0</td><td char=".">0</td></tr></thead><tbody valign="top"><tr><td>Groups (<italic>z</italic> scores)</td><td><20</td><td char=".">−1.62</td><td>Yes</td><td char=".">−1.53</td><td>Yes</td><td char=".">1.31</td><td>Asian</td><td char=".">−7.51</td><td>L4</td><td char=".">−2.43</td></tr><tr><td>21–24</td><td char=".">1.95</td><td>No</td><td char=".">1.12</td><td>No</td><td char=".">−1.04</td><td>Black</td><td char=".">0.64</td><td>L5</td><td char=".">−4.15</td></tr><tr><td>25–29</td><td char=".">1.61</td><td>PNS</td><td char=".">0.36</td><td>PNS</td><td char=".">−1.52</td><td>Mixed</td><td char=".">1.11</td><td>L6</td><td char=".">6.83</td></tr><tr><td>30+</td><td char=".">−0.52</td><td /><td /><td /><td /><td>Other</td><td char=".">3.27</td><td /><td /></tr><tr><td>PNS</td><td char=".">−2.44</td><td /><td /><td /><td /><td>PNS</td><td char=".">−3.4</td><td /><td /></tr><tr><td /><td /><td /><td /><td /><td /><td>White</td><td char=".">3.94</td><td /><td /></tr></tbody></table> </ephtml> </p> <hd id="AN0184922429-11">Stage 3: focus groups and thematic analysis</hd> <p>The thematic analysis led to the construction of three themes: challenging language; assessment criteria/feedback; and helpful staff interventions. Each of these themes will be discussed below, drawing on illustrative examples from the data.</p> <hd id="AN0184922429-12">Theme one: challenging language</hd> <p>Students expressed frustration with challenging and unclear language, with the words 'critical(ly)', 'assess', 'synthesise', and 'superficial' frequently noted as points of contention. This language arose in marking criteria, assessment questions, assessment guidance, and in feedback, meaning that for students it felt like there was no escaping these confusions. Students specifically discussed how language in assessments can be vague or ambiguous, which make expectations unclear. Students also referred to the relatability of the language used in assessment and feedback and how it can be challenging when they cannot easily relate to certain terms:</p> <p> <emph>So it's like "critical thinking". It's like throughout all of the assignments [...]. But I think it's a bit hard to really use it in the right way. So even though I have now finished the two semesters [...] if you ask me what is "critical thinking"? I mean, it's stupid hard to answer what it really is.</emph> </p> <p> <emph>For me, we've done a lot on critical writing, so we've had it explained [...] I guess it would be having those words explained in a way that you can sort of relate to.</emph> </p> <p>Students also explained there are times when individual terms themselves are understandable; however, the unfamiliar or challenging context in which the term is used (sometimes alongside multiple other challenging terms) can make it hard for them to understand expectations. This can lead to students feeling overwhelmed and frustrated by the task and needing to re-read and reflect on the instruction:</p> <p> <emph>It's not just [...] one word. It's the sentence in which it's written. Often you will read it and you think, I don't know what that means straight away, you sort of have to read it a few times [...]. So, for example, one of ours is "evidence of a highly structured approach with key information effectively identified, communicated and comprehensively analysed". So that sentence, you read that and don't think [...] I know what that means.</emph> </p> <p> <emph>I don't think you need to make the question as complicated and wordy and long as possible. I don't think that's part of the test [...], understanding the question shouldn't be part of your assessment.</emph> </p> <p> <emph>I didn't know how to assemble it, and I didn't know what was relevant [...] so that was extremely frustrating for me.</emph> </p> <p>Students also highlighted how diverse groups of students, notably new (Year 1) students, or students for whom English is not their first language, might be more likely to encounter challenges in interpreting assessment terminology:</p> <p> <emph>Within [assessment] tools, a lot of the language can be ambiguous, I think, particularly to a newcomer.</emph> </p> <p> <emph>I know there have been other students on the course where English isn't their first language, and they've particularly found sentences like that [a marking criteria example] difficult to understand.</emph> </p> <hd id="AN0184922429-13">Theme two: assessment criteria and feedback</hd> <p>In our survey, the quality descriptor terms such as good or excellent, had high confidence scores. However, in the focus groups the students explained that whilst the individual descriptors themselves are not necessarily problematic to understand, there is a challenge for them in distinguishing between marking levels and how to move between them, especially when the explanatory criteria to achieve a certain level contains challenging terminology:</p> <p> <emph>A 70 and 80, is for example, "good research", "excellent research", that's the difference. And I have no idea what that means [...] how can I go from good to excellent then?</emph> </p> <p> <emph>I think the language itself [...] is easy to understand. They don't use over complicated language [...] but if that tool is to help me [...] know what I need to do to go from 70 to 80, I don't think it does that.</emph> </p> <p>In common with previous studies our focus group data suggested that emotions can play a negative role and deter students from engaging with, conventionally written, feedback (Shields [<reflink idref="bib48" id="ref46">48</reflink>], Hill et al. [<reflink idref="bib21" id="ref47">21</reflink>]). This suggests that not only do staff need to pay attention to the language used in feedback, but also that there is a role to play in supporting student resilience to deal with the emotional aspects of assessment and feedback, i.e. to manage affect (Carless and Boud [<reflink idref="bib15" id="ref48">15</reflink>]):</p> <p> <emph>The feedback I received on some work I didn't do as well at, was just praising how bad it was. That's just like, I'm not gonna want to do any more otherwise, that's the reason I've enjoyed my [other] module a lot more, because they were nice about it.</emph> </p> <p>Finally, students also explained how the use of challenging terminology as part of their feedback limited their ability to apply summative feedback formatively for future assessment tasks, limiting their ability to learn from mistakes and improve in the future:</p> <p> <emph>It's not clear to understand what it is you can do with that feedback for the next steps.</emph> </p> <hd id="AN0184922429-14">Theme three: helpful interventions</hd> <p>This final theme explores how students have overcome challenges in interpreting the language used in assessment and feedback. After receiving written summative feedback students explained that they frequently would need to meet with their tutor to understand the comments which have been provided and how to take feedback forward to the next assessment:</p> <p> <emph>I know a lot of people on the course [...] have had to speak with whoever's marked it to go over the feedback because it doesn't often make sense.</emph> </p> <p> <emph>That's why it's important to get that time with your personal tutor, because if you don't understand the feedback from the comments [...], if you don't take the time to fully understand what they are saying, you will keep making mistakes.</emph> </p> <p>Clearly being able to engage with the marker and hear their rationale and explanation of terms helped the students engage with their feedback. In the focus groups one student also noted an occasion where audio feedback was provided which also helped meet this need:</p> <p> <emph>There had been one occasion that I have been able to hear the person that was grading my paper, they gave me like an audio for the whole thing. I still think that she graded me a bit harsh but like, at least it's like peace of mind, you know. So at least it gives you more to work on.</emph> </p> <p>In a formative context students noted occasions where they have been able to submit drafts of their work to tutors and receive formative feedback as being helpful. These formative opportunities allowed students to check understanding of task requirements and the language used in the assessment documentation. Alongside submission of draft work, students spoke of how specific sessions and activities helped them to understand assessment terminology and expectations prior to submission. Students explained how they feel it is often assumed that they would understand terminology and assessment requirements, and when they did not, they may feel embarrassed to voice their confusion. However, having support built into modules whilst completing a task, such as lectures, recorded videos, or drop-in sessions, helped students to understand terminology and assessment requirements and feel less awkward about asking questions:</p> <p> <emph>I like the approach of one of my module leaders, because she is recording this short video of going through the assignment brief, and then she is adding these little annotations [...] And I think it's great, because it's giving us some ideas of how to approach the assignment. And it may help us to notice such things in the future when approaching other ones.</emph> </p> <p> <emph>I think for me it would be helpful if [staff] went over the marking criteria and those words were explained, and then it gives [...] students the chance to question that if they're still not clear on certain words that come up.</emph> </p> <hd id="AN0184922429-15">Conclusions and implications for practice</hd> <p>This project sought to identify commonly used terminology in assessment and feedback documentation and how students' confidence in interpretation might vary. Previous research has emphasized there are many assessment-related terms which students find challenging (O'Donovan et al. 2004; Richards and Pilcher [<reflink idref="bib45" id="ref49">45</reflink>]; Butcher et al. [<reflink idref="bib13" id="ref50">13</reflink>]; Boyle et al. [<reflink idref="bib10" id="ref51">10</reflink>]). Building on this, Table 5 highlights commonly used assessment and feedback terms where students reported low confidence in interpretation. Conversely, Table 6 notes words where students have higher confidence in interpretation. These tables reveal a distinction in instructional terms with parallels to Bloom's Taxonomy (Bloom et al. [<reflink idref="bib7" id="ref52">7</reflink>]), where students are more familiar with instructions where they need to fundamentally demonstrate knowledge, compared to terms such as critical, interpret, and assess where students need to apply knowledge and critically evaluate and reflect.</p> <p>Table 5. Terms where more than 25% of respondents scored a term <3 (low levels of confidence).</p> <p> <ephtml> <table><thead><tr><td>Synthesise</td><td>Carefully</td></tr></thead><tbody valign="top"><tr><td>Superficial analysis</td><td>Examine</td></tr><tr><td>Abstract</td><td>Inform</td></tr><tr><td>Critical</td><td>Interpret</td></tr><tr><td>Reflective</td><td>Competent</td></tr><tr><td>Application of theory</td><td>Assess</td></tr></tbody></table> </ephtml> </p> <p>Table 6. Terms where more than 70% of respondents scored a term >5 (high levels of confidence).</p> <p> <ephtml> <table><thead><tr><td>Excellent</td><td>Weak</td></tr></thead><tbody valign="top"><tr><td>Exceptional</td><td>Define</td></tr><tr><td>Extremely</td><td>Inadequate</td></tr><tr><td>Outstanding</td><td>Explain</td></tr><tr><td>Good</td><td>Reference</td></tr><tr><td>Poor</td><td>Summarise</td></tr><tr><td>Fails to answer the question</td><td>Satisfactory</td></tr><tr><td>Successfully</td><td /></tr></tbody></table> </ephtml> </p> <p>As highlighted in the focus groups, the more challenging terms (Table 5) might be used in a range of assessment and feedback contexts, such as assessment briefs, written formative or summative feedback, or marking criteria. As these are multi-faceted and common terms, staff should take steps to engage students in dialogue about their meaning and encourage exploration of the terms to promote understanding through, for example, use of exemplars or an individual or class discussion.</p> <p>Our statistical analysis shows that different demographic groups might particularly find interpreting language difficult. We found that age and level of study (which in many cases might be related, however not exclusively) show notable differences; with younger students and those in lower years having lower levels of confidence in assessment language interpretation. To some extent, this is to be expected. As students' progress through their undergraduate studies, they will experience the assessment cycle frequently and therefore, where feedback is clear, understandable, and actionable for future tasks (the importance of which was noted in the focus groups), performance and assessment and feedback literacy should improve over time.</p> <p>We also found other significant demographic differences. For example, across all three terminology groups those who identified as of Asian ethnicity reported lower confidence scores than other ethnic groups. Students who identified as of white or black ethnicity had more variance in their responses. For example, white students had high confidence in interpreting the feedback terminology, but lower confidence in interpreting assessment instructional terms. Black students however reported high confidence in the assessment and feedback groups, but relatively lower confidence in the quality descriptor group. Students who identified as disabled consistently reported lower confidence than students who did not. These differences highlight the complexity involved in understanding language, and how groups of students will variably experience this challenge which may contribute to awarding gaps.</p> <p>In the focus groups, students reinforced that undertaking summative assessment is a high-stakes and emotional experience (Dowden et al. [<reflink idref="bib16" id="ref53">16</reflink>]), and receiving feedback can trigger both positive and negative emotions (Shields [<reflink idref="bib48" id="ref54">48</reflink>]; Winstone et al. [<reflink idref="bib53" id="ref55">53</reflink>]). Despite the perceived importance of feedback, there are situations where it might have negligible impact on student learning (Carless and Boud [<reflink idref="bib15" id="ref56">15</reflink>]). Our research demonstrates that where students struggle to interpret their feedback because of the terminology used, especially when in written form (Hill et al. [<reflink idref="bib21" id="ref57">21</reflink>]), frustration and demotivation can occur.</p> <p>Challenges clearly exist related to students' confidence in the interpretation of assessment and feedback terminology, which if not addressed will inhibit their ability to improve within and between assessment tasks and develop feedback literacy. Our students described interventions which have been adopted by staff which have helped them understand the terminology used in briefs and marking criteria. Importantly, students explained how these approaches enabled their understanding of feedback, providing a sense of closure on a task with actions for future improvement.</p> <p>Students appreciated occasions where staff created space within teaching sessions to work through and explain terminology and marking criteria. They also referred to where audio recordings of their tutor have been used to introduce a task and define expectations, but also for summative feedback. Being able to hear their tutor helped the students understand their task/feedback, allowing them to develop as learners. This aligns with previous research which has explored the benefits of audio recorded feedback (Lunt and Curran [<reflink idref="bib31" id="ref58">31</reflink>]; Voelkel and Mello [<reflink idref="bib51" id="ref59">51</reflink>]); however, it is important to acknowledge that audio-based feedback might not suit all students with differing learning styles (Sarcona et al. [<reflink idref="bib47" id="ref60">47</reflink>]) and so offering students flexibility or a combination of approaches might be needed.</p> <p>Students in the focus groups explained the need to often speak with tutors after work has been marked to decode their written feedback comments and the terminology used within. Dialogue has proven to be a successful means of ensuring there is a shared understanding, as meaning is socially constructed and co-created between student and tutor (Nicol [<reflink idref="bib40" id="ref61">40</reflink>]; Boud and Molloy [<reflink idref="bib9" id="ref62">9</reflink>]), building trust and mutual understanding (Matthews et al. [<reflink idref="bib35" id="ref63">35</reflink>]). It also allows for the foregrounding of emotions and through discussion a student-staff partnership is formed to positively work with the range of emotions assessment and feedback generates (Hill et al. [<reflink idref="bib22" id="ref64">22</reflink>]), such as frustration or demotivation due to not understanding terminology. Hill and West ([<reflink idref="bib23" id="ref65">23</reflink>]) demonstrate how dialogue can be implemented in a formative context, reducing the high-stakes nature associated with summative assessment. Such an approach might be effective to help students clarify the meaning of challenging terminology. However, this needs to be effectively designed into the student learning journey, and this approach is not without challenges related to engagement and resourcing (Hill and West [<reflink idref="bib24" id="ref66">24</reflink>]).</p> <p>It is important for staff to recognise the barriers students might face in decoding language and consider how different pedagogic approaches might be used to support student learning. The above pedagogic interventions have a common theme around staff creating the time and space within task and/or post-task to ensure that terminology and meaning is clarified, and a shared (or co-created) understanding exists. We suggest that creating the time and space for these opportunities is a form of compassionate pedagogy where staff and students share uncertainty and vulnerability around language (Arai and Tepylo [<reflink idref="bib4" id="ref67">4</reflink>]), creating an affective and motivational learning experience (Jazaieri [<reflink idref="bib26" id="ref68">26</reflink>]). In other words, the opposite of a situation where a student independently cannot interpret assessment terminology, resulting in demotivation and an isolated learning experience.</p> <p>It might be possible to implement a scaffolded approach to assessment and feedback interventions. For example, in the early years of study adopting a tutor-led dialogic approach, where instructional terms requiring higher level academic skills (such as criticality or reflectivity) are discussed and clarified, hopefully helping with the significantly lower confidence in understanding reported in this research amongst Level 4 students. This can then progress to more autonomous student-led approaches in the higher years as a student's learning and assessment/feedback literacy improves over time. Future research might explore how different support might be used in combination and implemented in a scaffolded, longitudinal model.</p> <p>However, it is important to note that, as implied above, additional space and time is needed to support students in decoding assessment terminology. This ultimately has staff resourcing implications. Creating opportunities for socially constructive and meaningful learning can be challenging under the cumulative pressures of the contemporary neo-liberal higher education academy, where increasingly performance-based metrics and competing demands can result in 'pedagogic frailty' where traditional assessment practices are maintained which do not fully support student learning and assessment/feedback literacy (Kinchin et al. [<reflink idref="bib29" id="ref69">29</reflink>]).</p> <p>One area which unfortunately, it was not possible to explore in this research was to what extent there might be disciplinary differences in students' understanding of assessment terminology. Disciplines define ways of thinking and practicing (Hounsell and Anderson [<reflink idref="bib25" id="ref70">25</reflink>]). There are discipline-specific concepts (Meyer and Land [<reflink idref="bib38" id="ref71">38</reflink>]) and signature pedagogies (Shulman [<reflink idref="bib49" id="ref72">49</reflink>]), resulting in members of a discipline sharing a common language (Healey et al. [<reflink idref="bib20" id="ref73">20</reflink>]). Such disciplinary differences may result in students encountering specialist terminology, or interpreting the language identified in this research through their disciplinary lens resulting in diverse meaning across subjects.</p> <p>Future studies might also continue to explore the differences in understanding of assessment and feedback language between students and staff, and between faculty. Understanding these differences is needed if challenges around assessment and feedback terminology (and the further issues they contribute to, such as awarding gaps) are to be addressed.</p> <p>To conclude, this research has undertaken a broad exploration of how students' confidence in interpreting assessment and feedback terminology might differ for individual terms and phases and between different student groups. Our results show that there are several commonly used terms which might prove problematic for students such as 'synthesise', 'assess', or being 'critical' or 'reflective' in their writing. We also explore different pedagogic interventions that allow tutors to work with their students to develop a shared understanding within and post-task, which used effectively can act as pivotal moments for students in developing assessment/feedback literacy, but we note such practices require the time and space within the curriculum and staff workloads for delivery.</p> <hd id="AN0184922429-16">Acknowledgements</hd> <p>The authors would like to acknowledge the team who have contributed to the success of the language of assessment project:</p> <p></p> <ulist> <item> University of the West of England: Laura Bennett, Cathy Minett-Smith, Jackie Chelin, Anne Harbin, Sabine Hassler, Nhi Ho, Judith Ritchie, Luke Rudge, Nicole Skidmore, Harry West, Mihaela Bachvarova.</item> <p></p> <item> University of Brighton: Lucy Chilvers, Juliet Eve, Jason Preston.</item> <p></p> <item> University of Greenwich: Catherine Emeordi-Okeke, Rachel George, Nikki Makinwa, Gemma Mansi, Jennifer Marie, Robert Wilson.</item> <p></p> <item> University of Hertfordshire: Marvelle Brown, Dorothe Diensthuber, Marjolein Groefsema.</item> </ulist> <p>The project team would also like to thank the QAA for their funding of the Collaborate Enhancement Project and their support with the dissemination of the work and development of the online resources linked above.</p> <hd id="AN0184922429-17">Disclosure statement</hd> <p>No potential conflict of interest was reported by the author(s).</p> <ref id="AN0184922429-18"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref30" type="bt">1</bibl> <bibtext> Supplemental data for this article can be accessed online at https://doi.org/10.1080/02602938.2024.2402960.</bibtext> </blist> </ref> <ref id="AN0184922429-19"> <title> References </title> <blist> <bibtext> Adcroft, A. 2010. 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Nicole played a key role in the focus group aspect of the project.</p> <p>Laura Bennett is based at University College Birmingham (and previously was Associate Director of Academic Practice the University of the West of England). Laura co-led this project.</p> <p>Juliet Eve is the Head of the Learning & Teaching Hub at the University of Brighton. Juliet led Brighton's involvement in this collaborative project.</p> <p>Cathy Minett-Smith is a Dean of Learning and Teaching at the University of the West of England. Cathy co-led this project.</p> <p>Luke Rudge is a Visiting Fellow with the Bristol Centre for Linguistics. Luke was actively involved in the initial stages of this project helping develop the methodological approach.</p> </aug> <nolink nlid="nl1" bibid="bib56" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib32" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib39" firstref="ref4"></nolink> <nolink nlid="nl4" bibid="bib55" firstref="ref6"></nolink> <nolink nlid="nl5" bibid="bib42" firstref="ref7"></nolink> <nolink nlid="nl6" bibid="bib18" firstref="ref8"></nolink> <nolink nlid="nl7" bibid="bib41" firstref="ref9"></nolink> <nolink nlid="nl8" bibid="bib45" firstref="ref10"></nolink> <nolink nlid="nl9" bibid="bib54" firstref="ref12"></nolink> <nolink nlid="nl10" bibid="bib23" firstref="ref13"></nolink> <nolink nlid="nl11" bibid="bib24" firstref="ref14"></nolink> <nolink nlid="nl12" bibid="bib44" firstref="ref15"></nolink> <nolink nlid="nl13" bibid="bib37" firstref="ref16"></nolink> <nolink nlid="nl14" bibid="bib34" firstref="ref17"></nolink> <nolink nlid="nl15" bibid="bib14" firstref="ref18"></nolink> <nolink nlid="nl16" bibid="bib52" firstref="ref19"></nolink> <nolink nlid="nl17" bibid="bib35" firstref="ref20"></nolink> <nolink nlid="nl18" bibid="bib43" firstref="ref22"></nolink> <nolink nlid="nl19" bibid="bib10" firstref="ref24"></nolink> <nolink nlid="nl20" bibid="bib13" firstref="ref25"></nolink> <nolink nlid="nl21" bibid="bib33" firstref="ref28"></nolink> <nolink nlid="nl22" bibid="bib27" firstref="ref31"></nolink> <nolink nlid="nl23" bibid="bib46" firstref="ref32"></nolink> <nolink nlid="nl24" bibid="bib19" firstref="ref35"></nolink> <nolink nlid="nl25" bibid="bib57" firstref="ref36"></nolink> <nolink nlid="nl26" bibid="bib30" firstref="ref38"></nolink> <nolink nlid="nl27" bibid="bib36" firstref="ref40"></nolink> <nolink nlid="nl28" bibid="bib28" firstref="ref41"></nolink> <nolink nlid="nl29" bibid="bib17" firstref="ref42"></nolink> <nolink nlid="nl30" bibid="bib11" firstref="ref43"></nolink> <nolink nlid="nl31" bibid="bib12" firstref="ref44"></nolink> <nolink nlid="nl32" bibid="bib50" firstref="ref45"></nolink> <nolink nlid="nl33" bibid="bib48" firstref="ref46"></nolink> <nolink nlid="nl34" bibid="bib21" firstref="ref47"></nolink> <nolink nlid="nl35" bibid="bib15" firstref="ref48"></nolink> <nolink nlid="nl36" bibid="bib16" firstref="ref53"></nolink> <nolink nlid="nl37" bibid="bib53" firstref="ref55"></nolink> <nolink nlid="nl38" bibid="bib31" firstref="ref58"></nolink> <nolink nlid="nl39" bibid="bib51" firstref="ref59"></nolink> <nolink nlid="nl40" bibid="bib47" firstref="ref60"></nolink> <nolink nlid="nl41" bibid="bib40" firstref="ref61"></nolink> <nolink nlid="nl42" bibid="bib22" firstref="ref64"></nolink> <nolink nlid="nl43" bibid="bib26" firstref="ref68"></nolink> <nolink nlid="nl44" bibid="bib29" firstref="ref69"></nolink> <nolink nlid="nl45" bibid="bib25" firstref="ref70"></nolink> <nolink nlid="nl46" bibid="bib38" firstref="ref71"></nolink> <nolink nlid="nl47" bibid="bib49" firstref="ref72"></nolink> <nolink nlid="nl48" bibid="bib20" firstref="ref73"></nolink>
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  Data: The Language of Assessment: Identifying Challenging Terminology for Students and Exploring Implications for Practice
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  Data: <searchLink fieldCode="AR" term="%22Harry+West%22">Harry West</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-2704-5474">0000-0002-2704-5474</externalLink>)<br /><searchLink fieldCode="AR" term="%22Nicole+Skidmore%22">Nicole Skidmore</searchLink><br /><searchLink fieldCode="AR" term="%22Laura+Bennett%22">Laura Bennett</searchLink><br /><searchLink fieldCode="AR" term="%22Juliet+Eve%22">Juliet Eve</searchLink><br /><searchLink fieldCode="AR" term="%22Cathy+Minett-Smith%22">Cathy Minett-Smith</searchLink><br /><searchLink fieldCode="AR" term="%22Luke+Rudge%22">Luke Rudge</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Assessment+%26+Evaluation+in+Higher+Education%22"><i>Assessment & Evaluation in Higher Education</i></searchLink>. 2025 50(3):381-395.
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
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  Data: 15
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  Data: Journal Articles<br />Reports - Research
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Vocabulary%22">Vocabulary</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation%22">Evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Feedback+%28Response%29%22">Feedback (Response)</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22Documentation%22">Documentation</searchLink><br /><searchLink fieldCode="DE" term="%22Language+Usage%22">Language Usage</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Esteem%22">Self Esteem</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22United+Kingdom+%28England%29%22">United Kingdom (England)</searchLink>
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  Data: 10.1080/02602938.2024.2402960
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  Data: 0260-2938<br />1469-297X
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  Data: Many interventions have been developed by staff to support students in understanding assessment task requirements and summative and formative feedback. However, to various extents, these approaches assume a shared understanding of the, often indeterminate, language used in assessment. This article reports on a project, which aimed to explore students' confidence in interpreting frequently used language in assessment and feedback documentation and explore ways in which staff can work with students to address misunderstanding and misinterpretation. To do this, we undertook a corpus-based linguistic analysis of assessment documentation to identify frequently used and potentially problematic language. We then used a survey and focus groups to explore with students their confidence in interpreting these terms. In doing so, we identify commonly used assessment and feedback terminology, which students find challenging to interpret, potentially resulting in frustration and demotivation. We conclude by exploring different approaches reported by students in the focus groups which help them interpret challenging terminology, notably different forms of dialogic-based intervention, but note, however, that time and space are needed within the curriculum for a shared (or ideally co-created) understanding of language to be developed between students and staff.
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