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celebrate dyslexia1st draft (Winter 2017/18)


Academic confidence and dyslexia at university


thesis graphic


Data and analysis

This section presents the core, data analysis of the information acquired through the research questionnaire.

The first part presents an overview of the demographics of the datapool showing the distibution of research participants by gender; study level, ranging from access or foundation year students through to post-doctoral researchers; study status being either home or overseas students; dyslexia disclosure and how these participants learned of their dyslexia. Commentary will be included that interprets these data in comparison to national statistics relating to students in Higher Education in the UK and also key points which emerge will be related to others' research and the underlying theory. This narrative process will continue throughout this section with the most pertinent discussion points being extracted and reviewed into the Discussion section of the thesis which follows.

This opening section is followed by a general desription of the statistical tools and processes that have been used to explore the data and the rationales that shaped the analysis. The next sections present in turn, details of the mechanisms that were employed to extract meaning from the data collected through the Dyslexia Index (Dx) Profiler section of the questionnaire and through the Academic Behavioural Confidence Scale. Following this, a detailed section presents the findings that emerged from analysis of the inter-relationships between Dyslexia Index and Academic Behavioural Confidence overall, but also how these metrics were more deeply explored through Principal Component Analysis and hence what this revealed when looking at a factors of Dyslexia and of Academic Behavioural Confidence presented as a matrix of inter-relationships.

Lastly, a short section will briefly discuss the data retrieved from the other metrics in the research questionnaire - that of the 6, psychometric subscales, why this is not included in the data analysis at this time and how this data might be explored as part of a future research project.

The Data and Analysis section concludes with a summary of the most important research findings which leads into the Discussion part of the thesis where explanations for them are suggested together with an interpretation about what they are revealing in terms of the relationships between dyslexia and academic confidence in university students.


Results and Analysis



Data was acquired following the deployment of an electronic questionnaire across the student community at Middlesex University both through an invitation-to-participate to all university students published on the university's 'home' internal webpage and also through a targeted invitation-to-participate to the specific cohort of students registered with the university's Disability and Dyslexia Service.

On completion of the questionnaire, submitting it generated an e-mail containing the complete dataset which was automatically sent to the researcher's university e-mail account. In total, 183 replies were received of which only 15 were subsequently discarded either because the questionnaire was less than 50% completed, or spoiled in some other way. Hence this provided a participant datapool of 166 complete datasets.

As reported in an earlier section, the questionnaire was very carefully designed to be an appealing, interactive, self-report webpage which incorporated innovative features that were intended to ensure that participant interest and hence engagement would be maintained throughout. The structure was divided into 5 sections which were accessed and viewable in turn, a design feature intended to reduce possible effects of questionnaire fatigue which might otherwise have occured should partipants have had sight of the complete questionnaire and hence perceive it to be lengthy and complex. This design approach, together with careful attention being paid to colours, contrasts and fonts, was adopted to try to ensure that the questionnaire was as accessible and dyslexia-friendly as possible.

The opening section collected minimal demographic data relating to gender, known learning challenges, student resident category and study status. Participants recorded their answers using selections from drop-down menu lists or selecting from check-box items.

The section which followed presented the Academic Behavioural Confidence Scale (Sander & Sanders, 2003, 2006, 2009) in its complete, 24-scale-item format with stem items unabridged nor modified in any way. Participants registered 'how confident they were that they will be able to ...' using an innovative sliding scale ranging from 0% to 100% (confident), hence replacing the conventional, 5-anchor-point Likert scale item recording process adopted in every other deployment of the Academic Behavioural Confidence Scale in research studies and projects to date. The rationale for this design approach has been discussed in the previous, Research Design, section.

On completion of the ABC Scale, participants were requested to work through the next section of 36 stem-item statements which were measuring the 6 psychometric scales of Learning Related Emotions, Anxiety regulation and Motivation, Academic self-efficacy, Self-esteem, Learned Helplessness, and Academic Procrastination. Each scale comprised 6 stem-item statements and participants also recorded their answers using continuous-scale sliders with end points of 0% and 100% agreement respectively. The detailed reporting of results recorded in this section and the subsequent analysis has been excluded from this thesis firstly because it became clear as a result of an early inspection and outline analysis of the complete datapool that sufficient data had been acquired through the ABC Scale and the Dyslexia Index Profiler to address the research hypotheses, and secondly that to include sufficient background literature review and later data analysis would have generated a finished thesis that would be in excess of submission limitations. Hence data collected in this section has been saved for later use in a subsequent research project.

The final section of the questionnaire to collect quantitative data presented the 20-point Dyslexia Index Profiler and the now-familiar continuous-scale sliders were presented to partipants for recording their % agreement with each of the stem-item statements.

Lastly, partipants were invited to qualify or enhance the data they had provided above by writing in an unlimited free-text area anything else about their learning challenges or strengths, or any other aspects about how they approached their studies at university. Entering data into this section was optional.

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The meanings of labels, terms, acronyms and designations used in the reporting and discussion of the data, results and analysis:

TERM abbreviation MEANING
datapool   the complete set of data acquired from all the participant questionnaires included in the project; n = 166
dataset   the complete set of data provided by one participant
research group RG a subgroup of the complete dataset
research group ND RG:ND the subset of the dataset containing participants who returned no disclosure of a dyslexia; n = 98
research group DI RG:DI the subset of the dataset containing participants who indicated that they were dyslexic; n = 68
Dyslexia Index Dx the value returned by the Dyslexia Index Profiler section of the main questionnaire. Dyslexia Index falls within the range 0 to 1000 with a higher score indicating a higher level of dyslexia-ness.
research subgroup DNI RG:DNI the subset of research group ND containing participants who returned a Dyslexia Index of Dx > 592.5 - this is the group of participants who returned no disclosure of dyslexia but whose Dyslexia Index suggests a high level of dyslexia-ness - hence these are the participants of greatest interest in this project -this is the INTEREST GROUP
research subgroup DI-600 RG:DI-600 the subset of research group DI containing dyslexic participants who returned a Dyslexia Index of Dx > 592.5 - this is the CONTROL GROUP
research subgroup ND-400 RG:ND-400 the subset of research group ND containing participants who returned a Dyslexia Index of Dx < 400
boundary value   this refers to the Dyslexia Index value which set the upper or lower Dx limit for determining a research subgroup. A report on how these values were established is provided in the previous section, Research Design.
Academic Behavioural Confidence ABC the value returned by the Academic Behavioural Confidence Scale section of the main questionnaire, falling within the range 0 to 100
  ABC-24 referring to the complete, original Academic Behavioural Confidence Scale of 24 scale items
  ABC-17 referring to the reduced, 17-scale item ABC Scale

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Datapool demographics

At the end of the questionnaire deployment period a total of n=182 questionnaire replies had been received. Of these, n=16 were discarded because they were more than 50% incomplete. The demographic distribution of partipants according to Research Subgroup; gender; student residency: home or international; and student study status: undergraduate (UG), post-graduate (PG), post-graduate research (PG-R), post-doctoral research (PD-R), attending a Foundation or Access Course (F/A), attending a Professional or Vocational Course (Pr/Voc), is shown in tabular and chart form below:

click to openDatapool and Research Subgroup: DI
datapool and RG DI
click to openResearch Subgroups: ND and DNI (Interest Group = subset of RG:ND)
research subgroup ND
click to openResearch Subgroups: ND-400 (= subset of RG:ND) and DI-600 (Control Group = subset of RG:DI)
research subgroups ND400 and DI600

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research groups pie charts1. Demographics of Research Groups and Subgroups

The charts show the relative sizes of research groups and subgroups as defined by the Dyslexia Index (Dx) boundary values, Dx=400 and Dx=592.5.

The top chart simply presents the proportion of students of the complete datapool (n=166), who disclosed their dyslexia on the research questionnaire (RG:DI, n=68) against those who indicated no learning challenges (RG:ND, n=98). A sample size of n=30 is widely considered to be the minimum for any reasonable statistical analysis to be conducted (Cohen & Manion, 1980) although it is accepted that there is no definitive ruling on sample size because the minimum value needs to be considered in the light of the proposed analysis (Robson, 1993). So by taking these advisories into account it is considered that a complete datapool sample size of n=166 with the two principal research groups dividing the datapool in the ratio 41%:59% (RG:DI, n=68 : RG:ND, n=98) the number of students who returned replies to the research questionnaire is sufficient for a meaningful statistical analysis to be conducted.

The second chart indicates the relative subgroup proportions of research group ND, that is, students who reported no dyslexic learning challenges. It can be seen that in accordance with the Dx boundary values set for the project, 18% of students in research group ND presented levels of dyslexia-ness that were more in line with students who had disclosed their dyslexia, as presented in the third chart which indicates more than two-thirds of the respondents who disclosed their dyslexia also demonstrated a level of dyslexia-ness above the critical Dx boundary value set at Dx=592.5. As reported in an earlier section (here) the most recent data acquired from HESA* (Greep, 2017) indicated that students in UK HE institutions who disclosed a learning disability accounted for 4.8% of the student population overall, this being a proportional rise of 50% from the figure quoted by Warmington (2013) for 2006. This is at least one further statistic which supports the observation of many studies that the prevalence of dyslexic students in UK universities is rising for a variety of reason not least through recent initiatives for widening participation in higher education amongst traditionally under-represented groups, particularly those with dyslexia who may have been previously disenfranchised from more formal education (Collinson & Penketh, 2010). Greep pointed out that this figure (4.8%) was an indicator of the incidence of all 'defined' learning disabilities and in addition to dyslexia, included others such as dyspraxia, ADHD and Asperger's Syndrome for example. Greep added that there is currently no mechanism in place in the current data collection process at HESA for discriminating students with dyslexia as a subgroup of those indicating learning disabilities and hence it is reasonable to suppose that the proportion of declared dyslexic students in the UK university population in 2013/14 is likely to be less than the 4.8% quoted, although Greep did indicate HESA's view that dyslexia is likely to be the most represented subgroup. It seems likely that this supposition is based on the generally accepted statistical evidence about the incidence of these learning disabilities more widely. For example, Casale (2015) quoted (unreferenced) HESA data which indicated that 5.5% of university students are disabled where presumably this figure included all disabilities of which learning disabilities are a subset, further claiming that dyslexia accounted for 40% of these students - that is, 2.2% of the student population as a whole. Casale drew a comparison with data provided by the British Dyslexia Association (2006) claiming that dyslexia is evident in approximately 10% of the general population of the UK but estimates of the prevalence of the traditionally considered dyslexia as a reading difficulty in children vary considerably with studies suggesting rates ranging from 5% to 17.5% (Shaywitz & Shaywitz, 2005)

Hence in the first instance it might be concluded that determining true levels of incidence of dyslexia either at university, in compulsory education, or especially in the general population is a challenging statistic to establish. This is certainly consistent with many of the arguments presented in earlier sections of this thesis discussing issues about how dyslexia is defined and hence relating to challenges in measuring it. As a result, it seems reasonable to conclude that it is as likely as not that the true proportion of dyslexic students at university is inevitably higher than the supposedly established data indicates. Secondly, the data collected in this project which, on the basis of the definitions of the metrics used, indicates that a substantial proportion of apparently non-dyslexic students may indeed present dyslexic learning differences - the 18% indicated in the second chart - adds to the weight of wider research and anecdotal evidence that dyslexia amongst university students is widely under-reported (Richardson & Wydell, 2003, Stampoltzis & Polychronopoulou, 2008) and/or continues to be unidentified on entry (Singleton et al, 1999).

*Higher Education Statistics Agency

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gender2. Gender

For the complete datapool, female research paricipants outnumbered males by a factor of approximately 2 to 1. That is, there were twice as many females as males in the datapool. (113:53 = 67%:33%, n=166).

Dyslexic student participants who were recruited from the targeted e-mail invitation sent out on the University's Dyslexia and Disability Service's e-mail distribution list and who subsequently were designated as research group DI were in the F:M ratio 53:15 (= 78%:22%, n=68) showing that female participants outnumbered males by a factor of more than 3 to 1, whereas student participants recruited through the open invitation to all students as published on the University's student intranet 'home' webpage, and who subsequently formed research group ND (n=98), were distributed by gender in the F:M ratio 60:38 (= 61%:39%) which although shows that female students still responded more positively to the invitation to participate than males when compared with the gender-analysed response rate, the female bias is lower.

In comparison to the gender distribution of students in the UK more generally, HESA* figures for the academic year 2016/17 for students enrolled on courses at HE institutions showed that although female students outnumbered males, the ratio is much closer to an even balance (F:M 57%:43%). For the UK generally, the ratio of females to males in the population as a whole in 2016 was F:M 51%:49% (Office for National Statistics). It is beyond the scope of this study to explore the reasons behind gender imbalances amongst higher education students however it is interesting to note the apparently significant differences in research participation invitation response rates between the two recruitment processes although the main reason for this may simply be that students registered with the University's Dyslexia and Disability Service may be heavily biased towards females. This at least would be consistent the argument that at university, male students are less likely than females to engage with learning development or support services either as a result of a known, hidden or unknown disability or learning difference or indeed for any other reason (Fhloinn et al, 2016. Kessels & Steinmayr, 2013, Kessels et al, 2014, Ryan et al. 2009) which is consistent with widely reported gender differences in levels of engagement with education and learning at levels and for a variety of reasons. This gender disparity has also been extensively observed and reported anecdotally within my own professional experience and domain of functioning in university learning development services however it is beyond the scope of this project to engage in a deeper analysis of the reasons behind these differences.




student residency charts3. Student residency status

In this project, participants were asked to identify whether they were a 'home' student or an 'international/overseas' student - that is, without separating non-UK EU students from all overseas students. The charts (right) present the distribution of research participants by domicile and for comparison, national data from HESA* for 2016/17 is shown. Although this demonstrates a similar distribution it must be added that the HESA figures are for student enrolment for that academic year rather than a measure of the domicile distribution of all students studying at UK institutions at that time. However, it is reasonable to assume that the ratio of 'home' students to non-UK students would not be significantly different were an aggregated figure to be available.

Hence the domicile distribution of the datapool in this study can be considered as representative of the wider student community studying at university in the UK.

However, when domicile distribution is considered at a micro- as opposed to macro-level it is interesting to note (from the data tables above) that only 3 out of the 68 participants in Research Group: DI identified themselves as non-UK students, a figure of just 4.4% which might be an indication of the very low incidence of non-UK dyslexic students studying at UK universities. It is beyond the scope of this thesis to conduct a detailed exploration to account for this, but it is likely that the reason for this apparently low figure may instead be an indication of the lack of available access to the university's Dyslexia and Disability Service for non-UK students with dyslexia. Hence very few non-UK students would have been on the Service's e-mail distribution list to receive the invitation to participate in this research project. The reason for this may be that as non-UK students are not eligible for formal dyslexia identification through the provision of the Disabled Students' Allowance in the UK and as such either may not be eligible to access the learning development and support provided by the Service to dyslexic students or may not even be aware that such a service exists. However it might also be the case that access to dyslexia idenfitication processes in their home countries for non-UK students is less prevalent than in the UK for a variety of reasons, a fact that might be supported in this research project by comparing the ratio of non-UK to home students for both identified dyslexic students (RG:DI) and apparently-unidentified dyslexic students (RG:DNI). For dyslexic students in research group DI this ratio is the 3 in 68 (4.4%) as mentioned above students sifted into research subgroup DNI as a result of their Dyslexia Index values of Dx > 592.5, the ratio is 3 in 18 (16.7%) which on the face of it suggests that there exists a significant proportion of un-identified, apparently dyslexic, non-UK students in this datapool at least. However as this subgroup is small (n=18) it would be inappropriate to draw significant conclusions from this disparity as it may be accounted for through margins of error. It would be necessary to establish a much larger subgroup of apparently non-dyslexic students who were presenting high levels of dyslexia-ness and hence examine the distribution ratio of 'home' to non-UK students to enable a more robust conclusion to be drawn.




level of study charts4. Student study status

It was considered useful to obtain data relating to the level of study programmes of students participating in the research not least to determine whether the research datapool constituted a reasonable cross-sectional match to the wider student community. If so, then it follows that conclusions derived from the research outcomes might reasonably be considered as a good representation of students attending UK universities more generally.

The charts present the proportions of student participants in the datapool according to level of their study programmes and comparisons with nationally collected data for 2016/17*. To enable a like-for-like comparison as far as is possible, those participants in this project who indicated study for professional or vocational qualifications were grouped with post-graduates, with post-grad- and post-doc researchers being combined. It is of note too that the national data labelled here as those studying at Foundation/Access level also includes those studying at pre-level 4 (1st year undergraduate).

From these it can be seen that in comparison to national data, undergraduate respondents in this study are over-represented although when undergraduates and foundation/access level students are combined, the proportions are closer (76% : 66%).

*HESA 2016/17 available at: https://www.hesa.ac.uk/data-and-analysis/students/whos-in-he, accessed on: 16 April 2018)




5. How dyslexic students learned of their dyslexia

my dyslexia sentenceIt was felt at an early stage in the research design process that part of the enquiry would try to find out more about how dyslexia becomes known to students who have declared it on their QNR response. This is important as one of the undercurrents to the project is the issue of the stigma associated with being labelled as dyslexic, especially the research hypotheses implicitly suggest that this may emerge as one of the factors that contribute to reduced Academic Behavioural Confidence in students with dyslexia compared to their peers. To explore this, QNR respondents who were declaring their dyslexia were also invited to complete a sentence in the opening section of the QNR to report how they learned about their dyslexia. The sentence required selections to be made from two drop-down menu lists so that on completion it would indicate how the respondent was informed about their dyslexia following screening or a full assessment. .

The summary grid below sets out this data from the 68 responses in research group DI. The grid total is 64 as 4 respondents in research group DI did not select options. The grid presents the number of respondents who selected particular combinations of options. For example, in the first row of the grid it can be seen that 2 respondents completed the sentence as: 'My dyslexia was DISCLOSED to me as a learning DIFFICULTY'. It is disappointing to note, although entirely expected, that the majority of students reported that their dyslexia was ‘diagnosed’ with diagnosed as a disability slightly ahead compared with disagnosed as a difficulty. It seems reasonable to suggest that the most appropriate way to report dyslexia to an individual should be to identify dyslexia as a difference as it would be expected that this might reduce the negative connotations of dyslexia being classified as ‘disability’ such that this is constructed in society more generally (eg: Connor & Lynne, 2006, Phelan, 2010).

dyslexia sentence analysis grid

It is of note that only two students out of the 64 who provided this information reported that their dyslexia was ‘identified’ to them as a learning ‘difference’. This may be an indication that assessors might usefully reframe the terminology that they use to more positively identify dyslexia to students and to move away from legacy descriptors rooted in a psychological determinism which strives to attribute dyslexia as a deficit rather than a natural occurrence of human neuro-diversity (Cooper, 2014). My view is that this adds evidence to the argument that it is a literacy-based education system that reduces those with a learning profile labelled as ‘dyslexic’ to a position of learning disadvantage, and so it is learning environments that need to be changed, rather then people with dyslexia, fixed. (See also: Thompson et al, 2015). It is also worth noting from the summary table that at least the number of students who reported their dyslexia as a ‘difficulty’ (n=31) was marginally higher than those reporting it as a ‘disability’ (n=26) which, given the stance of this project, is at least an indication of a slightly more positive approach to dyslexia being adopted amongst dyslexia assessment professionals.

By informing students about the results of a dyslexia screening or assessment in as neutral a way as possible, it is suggested that the internalization of dyslexia into the student's self-identity as being a ‘medical’ condition, implied by ‘diagnosing’ it, is likely to be reduced. To date, no other studies have been found which specifically explore the neutrality or otherwise of the communication process to the student concerned following a screening or assessment for dyslexia at university although some studies do examine the psychosocial experiences of receiving an identification of dyslexia. For example Nalavany et al (2011) claimed to have conducted the first study to explore how confirmed and self-identified dyslexia impacted on adult perspectives of their experiences associated with their dyslexia. This research was concerned less with how the adults in the research group (n=75) experienced the impact of their dyslexia on their learning and more so with how it affected their day-to-day lives however many of the participants recollected school and learning experiences that were 'hurtful, embarrassing, and scary, and that their teachers misunderstood their learning challenges (ibid, p74) which documents how the lasting effects of experiencing 'being different' in younger years persist into adulthood.

An important study by Armstrong & Mullins has already been referred to in the literature review section of this thesis but its main findings are particularly pertinent to this section despite their research datapool being adolescents at school or college rather than adults studying at university. Their study was also concerned with the psychosocial components of living with the label of dyslexia (ibid, p96) and although the outcome of their project led to the proposal of a fresh model for understanding how individuals assimilate their dyslexia into their self-identity (the Resistance-Accommodation Model), their model clearly has merit in advancing an understanding about the dyslexic self despite the study persistently referring to how individuals accommodated their diagnosis of dyslexia. The use of this phraseology did not appear to have been considered as a factor that might influence an individual's internalization of new knowledge about their dyslexia following its identification through a conventional assessment process, even though the authors did acknowledge that 'the amount of resistance or accommodation displayed by individuals clearly stems at least in part from their perception of dyslexia' (ibid, p99). My argument here is that this perception of dyslexia might also, in part, be influenced by the ways in which an identification of it is communicated and that has been the purpose of this part of the research questionnaire, albeit permitting just a cursory reflection on the meaning of the data produced. Thus it seems likely that as long as dyslexia remains perceived even as a 'difference' and hence dyslexic people perceive themselves as 'different', there will remain a stigma attached to the label. It is interesting to note however, that at least one research study concluded that an important process in understanding stigma associated with the labelling of difference is that the role of labelling needs deconstructing (Riddick,2000). One specific suggestion that emerged as a research outcome from this study was that the ownership of the labelling process by individuals concerned needs to have a focus on self-definition, personal understanding and elements of control (ibid, p665), which tacitly implies that part of the identification process (Riddick remains fixed on 'diagnosis' rather than identification) should include an element of positive counselling as part of the 'telling' procedures to the individual concerned so that the process of incorporating this new self-knowledge into the self-identity might be less psychologically unsettling. This is the view strongly argued for by Ho (2004) whose essay on the dilemma about labelling learning disability (dyslexia) supports the view that attributing a dyslexic identity to a learner can be as unnecessary as it can be counter-productive when the uniqueness of individuals' learning is taken as the context, further arguing that curricula and delivery need to be designed flexibly to accommodate this - a view that strongly resonates with the stance of this current research project. Mention of Riddick's and Ho's studies have been included as part of the discussion in an earlier section of this thesis (here).

So how does the data collected in this study from the 68 research participants who declared their dyslexia in the research questionnaire fit in with the commentary directly above? Questionnaire responses from students who disclosed, described or identified their dyslexia as a difference or a difficulty were sifted into a single subgroup with those whose dyslexia was diagnosed as as a disability or a difficulty being sifted into a comparator subgroup. (4 participants who declared their dyslexia but did not complete the declaration sentence). The table below sets out the summary of a statistical analysis to compare the mean values of Academic Behavioural Confidence overall and Academic Behavioural Confidence factors as determined from a principal component analysis of the complete datapool, a description of which presented later in this section (here). Student's t-test was used to determine whether these data presented a significant difference between means using a one-tail test, because we are testing the hypothesis that students whose dyslexia was disclosed/described/identified as a difference/difficulty present a significantly higher level of academic behavioural confidence than students whose dyslexia was diagnosed as a disability/difficulty; equal variances were assumed and tested using Levene's test. Arguably more interesting and more informative than t-test outcomes are effect sizes between means. Here, as with data analysed and reported below, Hedges 'g' is the effect size chosen and the rationale for using this over the more conventional Cohen's 'd' has been outlined in the previous section where the research methodology for the study was reported. For this analysis, an effect size of g < 0.20 is considered small to negligible, a value of 0.20 ≤ g < 0.45, small to medium, 0.45 ≤ g ≤ 0.6, medium, and g > 0.6 medium to large. Defining boundary values for effect size measures has not been pinned down, perhaps because this is a relatively new statistical measure that has only in recent years attracted interest amongst researchers in the particular fields of social science and in psychology. This has been discussed more fully above (here). In order to make the reporting of the outcomes more comprehensible and less repetitive, letter designations P,Q,R, have been added to the summary table so for example, table row Q presents the subgroup of students whose dyslexia was diagnosed to them as a difficulty and so forth.

dyslexia sentence table of results

The complete summary table presents interesting analysis outcomes:

  • looking at the summary row for the comparison of means between students whose dyslexia was disclosed/described/identified to them as a learning difference/difficulty (P) and those whose dyslexia was diagnosed to them as a difficulty (Q) there is a significant difference at the 5% level (p=0.0411) between the mean overall academic behavioural confidence, with an effect size of g = 0.64 which is medium to large; when the same first subgroup (P) is compared with students whose dyslexia was diagnosed to them as a disability (R) there is also a significant difference between the overall ABC means at the 5% level (p=0.0484) and a slighly lower effect size of g = 0.58. We might consider this to be surprising as it implies that there is a greater impact on academic behavioural confidence if dyslexia is diagnosed as a difficulty rather than as a disability. However, given the small sample sizes it is likely that this is within margins of error and the p-values and effect sizes are broadly the same. In order to examine this, the t-test and effect size calculations were conducted between subgroups Q and R (at the bottom of the table) and as expected, small or negligible effect sizes were obtained together with no significant differences between the overall ABC means nor ABC-factor means being established from the t-test.
  • hence the most significant (sic) results in relation to the discussion above are the comparision of means and effect sizes between the subgroups of students whose dyslexia was disclosed/described/identified to them as a learning difference/difficulty, and students whose dyslexia was diagnosed as a difference/disability (P, and Q+R). For the comparison of means for academic behavioural confidence overall, a significant result at the 5% level is indicated (p=0.0318) with a medium effect size of 0.59.
  • now discuss the ABC-factor outcomes

Hence it is suggested that further research in this area is appropriate if we are to gain a deeper understanding about how the dyslexic label impacts on students' approaches to their learning and it is in no small measure that this current project may make a useful contribution to this thread of enquiry as its key research hypothesis is principally concerned with exploring how dyslexic students' perception and internalization of their own dyslexia into their academic self might have an influence on their academic confidence in their studies at university.

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Statistical tools and processes

This sub-section

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Qualitative Data

This sub-section

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Other metrics

This sub-section

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Results summary


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Analysis summary


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