Keywords

Introduction

Universities have, for centuries, been the sources of wisdom and knowledge. In order to acquire this knowledge students used to travel to the universities where lecturers, masters in their field, would impart their teachings. Often the transfer of knowledge consisted in masters giving hour’s long monologues while the students passively listened and took notes. In order to be successful, this system requires from the student to: (a) attend to all learning sessions, (b) be able to record all the knowledge provided while listening to the lecturer and (c) understand and put in context (within their applications and implications) all information passively received during that unique offering of knowledge. This system puts in clear disadvantage many students who have learning differences, suffer from poor physical or mental health or have additional family/work commitments. Quality of higher education is recognized by researchers and governments to impact the student’s quality of life in the long term [1, 2]. The term “inclusive learning” is currently being widely used by academics and governments as a tool to improve the learning in those populations and therefore potentially improve the long-term quality of life of these students and dependants. However, inclusive learning as described by May and Bridger”… necessitates a shift away from supporting specific student groups through a discrete set of policies or time-bound interventions, towards equity considerations being embedded within all functions of the institution and treated as an ongoing process of quality enhancement” [3]. In the following subsections we define the current technological solutions to enable holistic inclusive learning.

This book chapter presents results of a study employing mixed methods and will focus on the role of different digital technology platforms in supporting assessment and improvement of inclusive learning in higher education. However, it does not systematically focus in detail on software specially developed to help students with learning difficulties. Rather, it presents and analyses recent advances in learning technologies that bring opportunities for inclusive learning and enable individuals to tailor the learning experience to their needs and abilities regardless of their degree of disability. Most of these platforms analyzed in here are relatively recent and while they charge per use, the majority also have a free version, which enables any educator to make use of them (with some limitations), as long as students and teachers have internet connection and a mobile device. In this chapter, we present results of our analysis and discuss design implications for technologies, which, if implemented effectively, will influence the assessment and improvement of learning and attainment of educational goals, as well as quality of life in the long term of any student.

Current Assessment Methods for Cognition/Executive Function, Attention, Memory and Learning in Healthy Populations

Before focusing on digital platforms that enable inclusive learning, we should take a quick look at the current assessment methods of cognition, executive function, including attention and memory and learning in healthy populations. The list of currently used tests used is very large and describing it into detail would take us away from the focus of this chapter. Table 13.1 describes a representative number of tests for executive function, attention, intelligence and different types of memory and academic resilience. We focused on tests that measure performance (PerfRO) [32]. Regarding learning, the best methods to test healthy populations are current academic assessments (e.g. written exams, coursework, oral presentations, group presentations, etc.).

Table 13.1 Representative listing of tests commonly used to measure attention, memory, executive functioning and intelligence
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Visual Tools

 

Tools

Consist in

S

Executive function

 

Approach/avoidance task (ATT)

Measures behavior when faced with a conflicting goal or event (which has both positive and negative characteristics or effects).

[33]

Working memory

 

Automated Working Memory Assessment (AWMA)

Fully automated online assessment of working memory.

[34]

Functional capacity/Executive function

 

Virtual Reality Functional Capacity Assessment Tool (VRFCAT)

Immersive virtual reality interactive gaming that measures functional abilities using realistic simulations of daily environments.

[35]

In this paper we focus on means of technology-enabled assessment and improvement of inclusive learning and quality of life in higher education.

Common Challenges to Inclusive Learning in Higher Education

Student’s ability to learn and fulfil their educational goals is affected by different, physical, mental (as defined by DSM-5 [36]) and situational challenges. It is estimated that on the UK, 3.5% of full time university students had a mental health condition in the 2017–2018 academic year. We will now discuss how each one of them impacts learning.

Physical Health and Illnesses

During their university studies a student might have periods of ill physical health or hospitalization. While in most cases the physical illness has a short duration (e.g., flu), some students might have long periods of illness (e.g., broken arm) or might live with chronic conditions (e.g., Chronic Fatigue Syndrome). In those cases, the student might not be able to attend university for periods of time. As a result, they won’t be able to take part in lectures, practical sessions or exams. They can also not engage with in-class activities, such as peer-assessment or debates. Additionally, students will struggle to submit paper-based coursework (although they may be able to submit coursework online). Moreover, if they are in pain (e.g., broken leg) the pain and/or pain medication might interfere with their concentration and sleep patterns. Finally, the injury or illness might prevent students from typing or taking notes.

Mental Health and Illnesses

While it is normal to feel sad or anxious at times, clinical depression and anxiety disorders can be crippling conditions, which can render the student unable to engage with their studies. Recent data shows that the mental health of students in higher education is deteriorating [37]. For example, a recent study from the Institute for Public Policy Research, reports that the number of first year students reporting a mental health problem in 2016 was 3 times higher than 10 years earlier in the UK [38]. As a result, there has been an increase in demand of Counselling and Mental Health services putting huge pressure on the universities’ and local welfare resources. In order to deal with this challenge, universities, governments and charities are trying to increase their mental health provision and there is a rising number of preventive campaigns. Additionally, there is an increase interest in initiatives, which aim to embed mental wellbeing within the curriculum [39]. These initiatives can be very varied, encompassing, from university-wide curriculum infusion, such as the Engelhard project at Georgetown University, USA [40] to focus on processes that might cause undue stress or disadvantage to some students (e.g. the use of lecture capture to revise lectures they were not well enough to attend or the use of anonymous online interactive tools to eliminate social anxiety).

The most common mental health disorders experienced by undergraduate students are depressive disorders (e.g. major depressive disorder, bipolar disorder or seasonal affective disorder), and anxiety disorders (e.g. general anxiety disorder or social anxiety disorder) [41]. A small percentage of university-age individuals experience other types of mental health disorders such as schizophrenia [41].

Depression is a common mood disorder that is characterized by constant sadness, lack of hope, motivation and energy, disturbed sleep patterns, and difficulties to make decisions [36]. As a result students feel that doing every day tasks is a constant struggle; they feel worthless and believe that their actions are useless and so their engagement with their studies suffers (they may stop attending lectures or might not be able to keep up with coursework or revision). At times they can become angry because they feel judged by others and themselves and believe they are falling short of expectations all the time. Their view of the world is pessimistic and they believe their situation will never improve. In extreme cases the student might plan and/or attempt to take their own life, although the percentage is lower compared to the general population of similar ages [42].

Bipolar disorder is characterized by periods when the student is depressed (see above for symptoms) alternated with “manic” phases, when the student is overexcited and overactive, but often doing tasks that are not productive nor make sense (e.g., writing for hours an essay about how to tickle ants when the assignment was on the habitat of insects that live in colonies) [36].

Seasonal Affective Disorder is very similar to depression, but usually only happens during a time of the year (e.g. in the European context, commonly during winter, when the days are short and often there is lack of sun) [36, 43]. Often students find particularly difficult to wake up on time in the morning, and have low energy levels during the day. As a result students might stop attending lectures and/or struggle to keep up with studies.

Generalised anxiety disorder is characterised by constant worry which leads to difficulties in concentration and/or sleep. In extreme cases students might develop panic attacks (for example in an exam) [36].

Students suffering from social anxiety worry disproportionately about social activities, such as going to class or speaking in public [36]. They feel judged at all times by others and fear that they will do something in public that is inappropriate. They are scared of criticism and can become paralised when others are watching what they are doing (such as giving a public presentation). In extreme cases students might develop social phobia, where they avoid interacting with others or speaking in public and/or experience panic attacks.

Schizophrenia is a severe mental disorder characterised by relapsing episodes of hallucinations (hearing or seeing things that do not exist outside their mind), disordered thinking, social withdrawal and cognitive impairment [36]. Students with schizophrenia may react in “odd ways”, sometimes believing that staff and/or other students are being bullies.

Learning Differences, Neurodiversity

Students’ intellectual ability can vary widely resulting in some cases in being diagnosed with a learning difference/disability (neurodiversity). Specific learning disorder is defined by DSM 5 as “a neurodevelopmental disorder with a biological origin that is the basis for abnormalities at a cognitive level” [36]. One essential feature of specific learning disorder is persistent difficulties learning keystone academic skills. In the 2015–2016 academic year, the Higher Education Statistics Agency reported 4.95% of all students in the UK enrolled in all higher education had a Specific Learning Difficulty [44]. These disorders are often diagnosed in childhood and are managed with the help of school teachers/advisers and/or specialised software/techniques. However, when students reach university, they might struggle with the transition into a less structured and/or supportive environment. University students with learning differences can use specialized assertive and adaptive technologies, which compensate for the decreased ability (such as TexthelpFootnote 1 or ClaroViewFootnote 2 and ScreenRuler,Footnote 3 which can help them reach their full academic potential [45]. There is a spectrum of learning differences as discussed below.

Students in the Autism spectrum or Aspergers find it hard to figure out what others are thinking or feeling based on their facial expressions and/or words [36]. Because of this they find socialising difficult. Noise or crowded spaces might be overwhelming for somebody with autism and thus sometimes they need to retire to a quiet space in order to calm down (they may also sit close to the entrance in class so that they can leave easily or might avoid crowded/noisy classrooms). They can seem awkward or feel uncomfortable in social situations, not making eye contact (resulting in appearing rude or patronising). Often they may take literally what is told to them (so they might struggle to understand jokes or sarcasm). Additionally, changes in their routine can cause them anxiety. Because of this they are very keen on having clear plans for everything that has to happen.

Students with dyslexia often mix up letters that have some similarity (like “b” and “d”) or words that have very similar spelling (e.g. “from” and “form”). As a result they often make spelling mistakes and are very slow readers/writers. They avoid reading and/or writing whenever they can (e.g. they will prefer a presentation than a written exam or coursework). They also struggle to write coherent notes during lectures (as they struggle to write while trying to understand what the lecturer is explaining and reading from the slides). However students with dyslexia can easily understand information when it is spoken to them and can explain themselves orally much clearer than in writing. Sometimes they struggle to follow directions (sequence of things that have to be done in a certain order) and thus find it difficult to organise and plan, which compound with their writing challenge results in students struggling to meet coursework deadlines [46].

Although Attention Deficit Hyperactivity Disorder (ADHD) is not considered a learning disability, it has at times a profound impact on the ability of the student to learn [36]. ADHD is characterised by difficulties in focusing (and lack of attention to details) and hyperactivity (which might make attending to long lecturers, of finishing coursework a challenge). At times, a student with ADHD might have difficulties coping with stress or remembering.

We should note that learning disabilities often do not sit in binary silos where the student either has a learning disability or not (with students often displaying different grades of a learning disability) [36]. Therefore, scholars are starting to strongly argue against the concept of “the average or typical student”. They reason that the students traditionally identified as having learning differences belong to the extremes of a continuum [47] and that we could consider that all students abilities are scattered across a spectrum of learning differences [48].

Students Juggling Higher Education with Work or Caring/Family Commitments

The majority of university students are relatively young (between late teens to mid 20s), do not have caring responsibilities (such as caring for young children or elder relatives) and do not need to work in order to fund their studies and daily life [49]. However, due to recent economic downturns and drastic increase in university fees, many students in higher education have to work while they study, in order to provide for themselves and/or finance their studies [50]. Moreover, due to an increased diversity in student population and the development of graduate entry courses, there is a slight rise in the number of university students with family and/or caring commitments, particularly within some vocational disciplines such as nursing [51]. These commitments might at times clash with their studies, preventing them from attending university (as they have to work or take care of somebody). Thus, at times, they may not be able attend lectures, practicals or exams. They might also struggle to submit paper-based assessments and can not benefit from taking part in in-class activities.

Method

In view of answering our research questions 2 and 4, we relied upon a mixed methods research approach based on literature reviews, surveys and interviews as shown in Fig. 13.1.

Fig. 13.1
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Research methods

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To get an accurate understanding of the problem definition, the research started with (a) reviewing the most common learning challenges using the Diagnostic and Statistical Manual of Mental Disorders (DSM–5) as primary source and selected literature as secondary source (presented in the previous section). We then built upon a (b) recent literature review [52] to gain a deeper understanding on the role of information technology (IT) in education as well as a description of digital learning platforms and the evolution of learning management systems (LMS). (c) We then surveyed eight faculty members (see table below) to gather current uses of digital learning platforms (Table 13.2). We asked them the three following open-ended questions: (q1) “What digital platforms or tools do you use for your lectures?” (q2) “What makes these platforms or tools attractive?” and (q3) “What other platforms would you recommend and why?” (d) By means of interviews, we then asked the same questions to one course director and three learning designers to gather their experiences of state-of-the-art tools for inclusive learning. The interviews allowed us to derive four digital learning tools categories, categorized independently by the co-authors of this paper. (e) In order to analyze the commonalities and differences across these four categories, we used the Business-Application-Information-Technology (BAIT) model. We then summarized our findings by refining the seven principles of the Universal Instructional Design [53, 54] framework for the context of inclusive learning.

Table 13.2 Profiles of survey participants in step (c) and (d)
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Digital Learning and Teaching Platforms (DLTP) Description and Analysis

Along with the almost universal access to personal computers and smartphones, Internet and web applications have disrupted education [52]. Not only have they changed the way knowledge is transferred and learnt, but also the dynamics between lecturers and students as well as among the students. From our interviews with learning designers (Table 13.2), four categories of digital learning and teaching platforms have emerged, as potential enablers for the assessment and improvement of inclusive learning: Learning Management Systems (LMS), Social and collaborative tools, In-class interactions and Out-of-class interactions.

Learning Management Systems

LMS are software applications designed with the specific intent of assisting instructors in meeting their pedagogical goals of delivering learning content to students [55]. Available as web application by means of an Internet browser (Figs. 13.2 and 13.3), LMS have disrupted the way students access (digital) lectures, communicate with their lecturers, classmates and other learning communities, access course materials, take online quizzes and submit their assignments [56]. From the lecturer’s point of view, LMS allow to organize classes, publish course materials, create and grade assignments among many additional features. Our interviews revealed two types of software applications: Open-source with MoodleFootnote 4 being on top of the list and GraaspFootnote 5 in the role of outsider [57]. On the proprietary side, CanvasFootnote 6 was the most cited. In our case, LMS were used to structure and describe lectures, upload and share documents, lecture recordings and tutorials as well as post and submit assignments. Uploaded files are presentation slides, PDF and text documents. Our survey revealed that LMS are mostly accessed via desktop or laptop computers.

Fig. 13.2
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Canvas LMS—Assignments View of a Class (Under the license: https://creativecommons.org/licenses/by-sa/3.0/deed.en)

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Fig. 13.3
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Moodle—Class View

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Social and Collaborative Tools

Social and collaborative tools are defined as (web-based) applications that allow users to create and to share online documents, spreadsheets, presentations, and forms [58]. They are mostly used by students to create and share content such as assignments. Similar to LMS, open-source and proprietary tools are being used. The two most used are respectively Google DocsFootnote 7 and Microsoft Office 365.Footnote 8 They allow students to create different types of documents from presentations to spreadsheets and letters and work simultaneously on the same documents (Fig. 13.4). As part of Microsoft Office 365, Teams offers new opportunities for lecturers to engage with students, and also for creating groups amongst students. It provides instant messaging capabilities, both via text and video, enabling lecturers and students to communicate regardless of their location. In addition, it offers live captions to help students with hearing impairments. Newcomers such as PadletFootnote 9 are increasingly used in class for students to publish their work and collect feedback (Fig. 13.5). These tools are most of the time accessed from a desktop or laptop computer while a mobile interface is also available but difficult to use .

Fig. 13.4
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Padlet—Main View (shared amongst groups or students)

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Fig. 13.5
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Google Doc—Collaborative work (Under the license: https://creativecommons.org/licenses/by-sa/3.0/deed.en)

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In-Class Engagement

As stated in Holzer et al. 2013 [57], interactivity in person classrooms is considered an important success factor in learning but it remains very challenging to promote. Simple technologies such as the Clickers (that combine hardware with software) gained popularity in classrooms for their ability to gather anonymous answers to questions asked in class [59]. It gives the lecturer a chance to immediately assess the students’ knowledge and quantitatively measure the progress of the class (Fig. 13.6). The in-class engagement tools are seen as the next generation of interactions by allowing lecturers and students to send anonymous text messages in addition to creating polls (Fig. 13.7). They are mostly used by lecturers to gather feedback from students and to encourage them to engage in lectures/workshops/seminars. A few tools were revealed by the survey: Speakup,Footnote 10 which was developed by two Swiss universities and available free of charge; SocrativeFootnote 11 and SlidoFootnote 12 that offer similar functionalities than Speakup; MentimeterFootnote 13 that also allows for the creation of pools but requires a subscription for intensive usage; and KahootFootnote 14 that leverages the concept of gamification. All these tools are available as web and mobile applications and are most commonly used from a smartphone and laptops.

Fig. 13.6
figure 6

Mentimeter—Live question/answers

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Fig. 13.7
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SpeakUp—Live question/answers

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Out-of-Class Interactions

Out-of-class communication channels widely depend upon the university, the faculty/school (discipline) and the culture. Most of the course communication and feedback relies on emails or on LMS (e.g., class forums). Tools such as MS Teams,Footnote 15 Speakup or Slido are also used after the class whereby lecturers or students give feedback (Fig. 13.8). Recently WhatsappFootnote 16 and other text message applications have become very popular amongst students to exchange tips and documents. These latter tools are easier to access and to use, thanks to their integration in smartphones.

Fig. 13.8
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Ms. Teams—Discussion panel

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Within and Cross DLPT Analysis

Table 13.3 summarizes and analyzes the differences and commonalities of the identified DLTP. As analysis framework, we used the Business-Application-Information-Technology—BAIT model [60]. The latter is used to logically and functionally describe a system and its dependencies. More specifically, the Business layer looks at the business rationale and the processes that follow from it; the Application layer investigates the organization of capabilities and functions; the Information layer looks at the data models; and the Technology layer investigates the implementation of logic, standards, bundling and tooling. For a more distinct analysis across the DLTP, we adapted the BAIT model as follows: The Business layer became the teaching process. We added a File layer to represent the types of file managed by the system and a Medium layer to be able to better differentiate the medium used to execute the application.

Table 13.3 Platforms listed by the surveyed faculty
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Assessment and Improvement of Inclusive Learning with Digital Learning Platforms (DLTP)

The analysis above sheds light on the types of application used by a selected sample of lecturers. Though it helps identify what applications and functionalities are the most popular DLTPs, the following critical question remains: How much do these learning platforms and applications support inclusive learning, and how it can be evaluated based on the data originating from these platforms? To answer it, we proceeded as follows: First, we extracted the challenges linked to inclusive learning as described in the section above. Second, we classified the challenges along three impairments—i.e., physical that refers to a student’s physical limitation to follow a course; cognitive that refers to a student’s potential troubles to remember, learn new things, concentrate, or take decisions and behavioral that refers to inability for a student to build or maintain satisfactory interpersonal relationships with his or her classmates and lecturers (Table 13.4). Third, we mapped these impairments to functionalities provided by digital learning platforms and tools and reasoned upon their assessment functionalities based on the data originating from the application logs (Table 13.5). Finally, we suggested potential implications and functionalities for some of the unmet challenges based on our focus groups with learning designers (N = 3).

Table 13.4 Inclusive learning conditions and system requirements
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Table 13.5 Map between system requirements and DLTPs
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Physical Impairments

Physical impairments are divided into two subcategories: (a) The inability to attend classes or exams, caused by injuries, care commitments or illness, and (b) some limitations that prevent students to hear, type or see. For the former (a), DLTPs should allow students to access teaching materials regardless of their location, as long as they have an Internet access. The policy with regards to video-recording of the lectures depends very much upon the university. In some cases, all classes are recorded, while the opposite is also true. Traditional universities are afraid that students would not attend classes if they had online access to such content. Given that some students might not return to classes for several months, the ability to view lectures and write exams remotely is critical. Software applications such as ExamsoftFootnote 17 or RogoFootnote 18 that provide an Internet-based safe environment are increasingly used by universities (particularly during the Covid pandemic). On the other hand, students suffering from hearing, typing or visual impairments (b) are not offered much help from DLTPs. Though collaborative tools such as Office 365 embed “read aloud” and “dictate” functionalities for Word and Excel, it is often not the case for slide-decks (e.g., PowerPoint) that require the lecturers to manually add captions. Similar problems can occur with PDFs documents depending on the original format and the conversion process. Moreover, video captions are also very rarely added by lecturers and when added the caption software can make mistakes (particularly when scientific terms and acronyms are used). However, some applications such as Microsoft Teams allow for live captions. Lastly, students who have difficulties using a keyboard do not receive much support from DLTPs. Although there exist additional software applications such as DragonSystems,Footnote 19 they would only partially fulfill the tasks of a student. As an alternative, in-class engagement apps can also be used post-lecture to continue discussions that occurred during lectures . To conclude, multimodal access to content is currently missing.

Cognitive Impairments

Cognitive impairments refer to students who have difficulties focusing, remembering and those who are slow readers and mix up letters. It can also be side effects from anxiety, stress, depression or medication taken for physical or mental health disorders such as pain or schizophrenia. In both cases, online access to teaching materials and video-recordings in particular, brings many advantages. Students can learn at their own pace, moving back and forth until they have acquired the knowledge. However, LMS and other platforms fail at two levels: (a) in providing tailored learning experience, assuming that each student has the same learning capacity, (b) in assessing the condition and providing exercises to support the students. Similar to guidelines for people suffering from physical impairments (e.g., minimum font-size, reduced amount of length, prioritizing images), digital learning platforms have the opportunities to implement machine learning driven quizzes that adapt the questions to the learners as well as adapt the content presentation (e.g., learning section) too. In parallel, students can also use wearables to track their biometrics and thus have a more objective assessment of the impairments.

Behavioral Impairments

Students with disorders such as depression, anxiety, autism or schizophrenia display some behavioral impairments that prevent them from fully engaging with the learning. They sometimes have access to support workers that take notes for them or extra time during assignments. They also sometimes have access to “safe” environments such as dedicated rooms for them to calm down in case of a sensory overload. Aside from this, tools such as Speakup offer safe digital space in which students can anonymously ask and answer questions without the fear of being individually criticized or judged. For students whose behavioral impairments prevent them from attending lectures or can attend only partially, remote access to teaching materials (e.g., video-recordings or slides) significantly increases the students’ chance to succeed. In this view LMS plays an important role as central platform for content access but also for handing in assessments and receiving potential feedback and discussions such as in forums.

What Do DLTPs Support? What Remains Unsupported?

In order to analyze the means by which DLTPs address the identified inclusive learning conditions summarized in Table 13.4 , we extracted the system requirements from the same table and mapped them to functionalities provided by the currently used, digital learning platforms and tools. We added a column opportunities to demonstrate how technologies beyond our scope of analysis can support inclusive learning. The results are presented in Table 13.5 . The first column of the table, R#, refers to the system requirements presented in Table 13.4. We also differentiate between technologies that assess or directly address the condition (in dark grey) and those that mitigate (in light grey) the condition. For instance, condition R#—difficulties coping with stress and anxiety: DLTPs offer functionalities to mitigate the condition by means of asynchronous teaching that allows students to review the knowledge as many times as required, and offline and anonymous communication that allow students to be protected. On the other hand, wearables and mobile apps relying on biometrics and self-reporting allow for a quantitative assessment of the level of stress.

When looking at the table above, it is clear that the coverage of inclusive learning’s needs by the identified DLTPs is very limited. Most of the platforms rather mitigate (dark grey) than assess and improve the different conditions. Apart from providing distance learning capabilities required for students who cannot access the facilities, the tools fail in supporting behavioral and cognitive impairments. Let us take stress problem as an example: though some of the learning designers we interviewed have setup dedicated pages and modules in LMS to provide links to specialized websites, DLTPs do not support students in assessing and helping with their stress overload. However, while a considerable number of techniques, approaches and a significant number of mobile applications a at the moment, DLTPs do not provide any integration for these applications. For some of the challenges for learning, we identified specialized tools/apps that are already on the market. However sometimes it might be challenging to embed them within the existing learning technologies. Some of the current technologies are starting to address this issue (i.e. Moodle “accessibility checker ” and “screen reader helper ” as shown below (Fig. 13.9).

Fig. 13.9
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“Accessibility checker” and “screen reader helper” currently embedded within the LSM system Moodle

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Additionally, in some cases the challenges faced by students require medical intervention (e.g. psychosis or depression). In these cases the teaching apps should facilitate learning, but they can not replace medication and/or talking therapies. For the majority of the conditions, assessment capabilities are available with external applications (light grey). Very often these applications and platforms have been scientifically evaluated.

Supporting Inclusive Learning: Implications for Design of Future Platforms

Increasing access to learning has been the focus of a great deal of research. The Universal Instructional Design (UID) is certainly the most comprehensive [69]. It builds on the concept of Universal Design to identify and eliminate unnecessary barriers to teaching and learning while maintaining academic rigor. UID is therefore described as a process that involves considering the potential needs of all learners when designing and delivering instruction. We used the UID as framework in order to refine the seven UID principles for the purpose of inclusive learning. Our inclusive learning principles, presented in Table 13.6, build upon the analysis that we presented above as well as the survey and the interviews we conducted.

Table 13.6 Universal Instructional Design applied to inclusive learning
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Discussion

There is no doubt that information technology is transforming education. When used for assessment and improvement of inclusive learning, it offers a wide range of opportunities for students suffering from behavioral, physical and cognitive impairments. Beyond the application’s functionalities and goals, from our data and own observations, we identified five key elements for a successful implementation and uses of digital platforms and tools that assess and improve the individual’s inclusive learning. The discussion part ends with some limitations and a note to the significant positive impact that information technology to enable teaching and learning during the Covid19 pandemic.

Assessment vs. mitigation of the conditions

Apart from physical impairments that are not necessary expected to be assessed via DLTPs, behavioral and cognitive impairments are not assessed by DLTPs as shown in Table 13.4. They rather provide limited functionalities to mitigate the conditions such as “read aloud” for students suffering from visual impairments. Though logs from DLTPs can be used in order to assess the number of interactions between students and teaching material for instance, this functionality has its limits. It will not inform the lecturer whether the student has read or understood the lecture, but only that he had opened it. However, a huge number of opportunities come from mobile applications as well as wearables that rely on either biometrics or self-reporting to provide objective assessment of the conditions. This is notably the case for stress and anxiety, attention loss and memory retention’s problems.

Usability

Research has looked into the usability of digital learning platforms and learning management systems in particular. As stated by Harrati et al. (2016), “Positive user experience is of prime importance for educational learning systems playing vital role for the acceptance, satisfaction and efficiency of academic institutions” [70]. Usability of digital learning platforms has drawn the attention of many researchers after universities and schools complained that the tools do not bring the promised outcomes and that they are not used appropriately. For example, it is not uncommon for universities to install plugins for improving user interface’s ease of use. For a successful implementation of digital learning platforms, it is then critical for the solution provider to focus on user-centeredness (e.g., lecturer, student). Though most LMS embed functionalities to interact in classes and create pools to engage with students, all lecturers that we interviewed use additional applications for their high usability and accessibility. It is even more important in the case of inclusive learning due to students’ potential impairments.

Integration in the lecture design

It is not sufficient to equip lecturers and students with digital learning platforms and tools. The latter must be fully integrated in the course and curriculum design. Video-recordings as well as in-class engagement activities must be part of a wider program aligned with learning objectives.

Integration in the enterprise architecture

In-class engagement apps as well as collaborative tools are rarely integrated with learning management systems. Beyond technical challenges, they require taking additional steps (e.g., different logins, user interfaces, terminologies) that become confusing for students with cognitive impairments. Universities therefore have to ensure that the same terminologies and descriptions are used. As mentioned above, one system (e.g., LMS) must play the role of central hub from which students can access every other application.

Platform monitoring

Once in place, the adoption and usability of the platforms have to be closely monitored, also serving for an assessment of the inclusive learning path, i.e., the learning path of the individual. For each impairment category, champions amongst students have to be identified and their uses (e.g., logs) analyzed. Together with the lecturers, learning designers and software providers, universities have to collaborate to ensure that the functionalities meet the student needs. Although it might sound trivial, it is much often not the case as highlighted by the learning designers we interviewed.

Assessment and impact on quality of life

In their current implementations, digital learning platforms are designed to assist rather than assess students’ quality of life. Following the Quality of Life Technologies’ definition [71], DLPT are limited in two areas. First, in quantitatively assessing and informing the students with regards to their improvement in any of the three impairments: physical, behavioral and cognitive. To date, only the total (sum up) mark for all assessments in a subject/course/module can be used to assess any type of progression. Though time spent on lectures, number of submission’s attempts, number of typos could potentially be used to evaluate a student’s progress, this information is not available to students nor educators. Second, in integrating data from sensors, activity trackers and mobile devices, students (and potentially parents) and teachers have a chance to either detect or follow up on some conditions and quality of life in particular using quantitative data [72]. In addition to questionnaires that are given to students at the beginning of the semester to assess e.g., stress and anxiety, the integration of continuous data from sensors in the LMS could help students, parents and schools to quantitatively analyze students’ progress and more importantly find correlation between changes in quality of life and impact of academic results.

Digital therapeutics

Some behavioral conditions such as stress, anxiety and depression, digital therapeutics are seen as a new type of (mobile) applications that are either used to complement medication or to replace it. Described as “evidence-based therapeutic interventions driven by high-quality software programs to prevent, manage, or treat a medical disorder or diseaseFootnote 20”, some of these applications have already been approved by the U.S. Food and Drug Administration. Building on Cognitive Behavioral Therapy, these applications engage with their users on a daily basis while using objective data to assess and customize digital treatments [73]. These applications could be seen as an alternative or a complement to counselling sessions.

Overcoming learning ability? Limitations

Technology, and in particular the apps/programs discussed this chapter, is not the only solution to facilitate inclusive learning. Often students benefit from a combination of multiple high-tech and low-tech approaches, tailored to their unique needs. For example, there is software specially developed to help students with learning difficulties (such as Optical Character Recognition software to help students with dyslexia or talking calculators to help students with dyscalculia), which has been widely reviewed on [45, 74]. Another example is granting extension on coursework deadlines to enable students with dyslexia the extra time they may need for proof reading or to provide a student with a broken arm time for their arm to heal, so that they can write the coursework. Additionally, students with mental health disorders (poor mental health) often require medical treatment aimed to heal their condition, such as medication and/or counselling, which has little to do with the platform capabilities. Another word of caution included a comment that “There are many other apps, but they tend to behave similarly to the ones we analyzed” (comments from a learning designer), indicating that the platforms need proof of authenticity.

Impact of information technology on teaching and learning during the Covid19 pandemic

Although most of the content of this book chapter was written before Covid19, we could not conclude this chapter without referring to the role that information technologies have had in ensuring a seamless transition into online-only teaching during the pandemic. Within weeks universities had to migrate all their learning and teaching activities to online-only provision. From discussions with colleagues across the world we have learn that level of previous familiarity with LMS and applications (and “willingness to change” of members of staff) impacted the speed and success of the migration. However, regardless of previous preparation, all universities had to transfer as much teaching as they could online, with MS Teams suddenly being used by lecturers and students across the globe, often with just hours or minutes to learn how to use it. An extreme case was seen at the School of Veterinary Medicine and Science, Nottingham University (UK), which achieve a full-online start of the academic year for their April 2020 intake, with lecturers having only a few days’ notice to migrate online their teaching delivery. At the time of writing of this article, we could see that across the world academics have adapted their courses to distance and Covid-secure teaching, using a mixture of online delivery/assessment for any subject that can be taught remotely and in person Covid-secure teaching for activities that must happen in person, e.g. nursing practical teaching [75].

Conclusion

Universities have a long history of trying to offer education to students who have different needs [76, 77]. However, regardless the technology used or the teaching method, it is interesting to observe that students sometimes complain; for them a “proper” lecture is sitting on a chair for a couple of hours while listening to the lecturer’s monologue that tells them what they need to know in order to pass the exam. Though digital learning and teaching platforms do support assessment and improvement of inclusive learning and teaching, which may influence the wellbeing and quality of life of the students, for a sustainable impact, changes in mindsets have to take place for both, lecturers and students. These platforms became an unexpected blessing and saving grace when the world faced the Covid19 pandemic. We are yet to know the real impact of these new practices on the long term learning outcomes and life quality of the individuals influenced by these radical and unexpected changes.