Communicating with Information: Creating Inclusive Learning Environments for Students with ASD – In the Library with the Lead Pipe Skip to Main Content Open Menu Home About Awards & Good Words Contact Editorial Board Denisse Solis Ian Beilin Ikumi Crocoll Jaena Rae Cabrera Kellee Warren Nicole Cooke Ryan Randall Emeritus Announcements Authors Archives Conduct Submission Guidelines Lead Pipe Publication Process Style Guide Search Home About Awards & Good Words Contact Editorial Board Denisse Solis Ian Beilin Ikumi Crocoll Jaena Rae Cabrera Kellee Warren Nicole Cooke Ryan Randall Emeritus Announcements Authors Archives Conduct Submission Guidelines Lead Pipe Publication Process Style Guide Search 2020 1 Apr Frederick Carey /0 Comments Communicating with Information: Creating Inclusive Learning Environments for Students with ASD In Brief The focus of this article is twofold: it 1) considers how digital humanities techniques and methodologies increase accessibility and scholarship opportunities for students with Autism Spectrum Disorder; and 2) outlines how libraries can collaborate with existing services to provide subsequently appropriate supports for students. Autism Spectrum Disorder (ASD), one of the increasingly prevalent manifestations of neurodiversity within higher education, presents significant challenges to students interacting with academic resources and producing traditional scholarly outputs. Traditional scholarship presupposes that students possess a certain level of ability to interact with their course materials, analyze that interaction, and then write both about their interaction and analyses. However, limitations in working memory and Theory of Mind create additional barriers for students with ASD in meeting these presumptions. Fortunately, emerging scholarly practices within the digital humanities now provide more equitable mediums for scholastic output as well as new opportunities for students to access and interact with course content and materials. While current structures within academia presuppose that students are able to interact with materials in a specific way, libraries are uniquely positioned to collaborate with constituent departments and services across campuses of higher education to teach students emerging strategies to more effectively interact with scholarly materials. By Frederick C. Carey Introduction Institutions of higher education not only offer students the academic freedom to cultivate intellectual interests and develop skills that they can hone into lifelong careers, but they also establish social and professional expectations that provide the foundations for sustained success. As such, students are expected to interact with social and professional networks both in person and virtually. However, studies show that perpetual connectivity through social media and other technological platforms contribute to increased cases of stress, anxiety, and depression.1 Therefore, institutions of higher education support students’ needs in these areas by offering mentoring, mental health, and transitional services to better equip students to successfully adapt and thrive within their new environments. The effectiveness of these services, however, are explicitly connected to the makeup of the student population they serve. Currently, student populations across higher education continue to grow increasingly neurodiverse2 , and as such, both social and academic services have been institutionalized to meet student needs. Institutions provide supports for transitioning into new routines; navigating new social structures both in and outside of classroom settings; managing fatigue and sensory overload; treating anxiety, depression, and stress; as well as developing executive function (EF) skills related to planning, organizing, and prioritizing information; self-monitoring; self-regulating; and creating time management plans. These services are essential for acclimating to the social and professional structures of higher education and post-collegiate life, but do not provide all the tools neurodivergent students need to succeed in academia. Autism Spectrum Disorder (ASD), one of the increasingly prevalent manifestations of neurodiversity within higher education, presents significant challenges to students interacting with academic resources and producing traditional scholarly outputs. Traditional scholarship presupposes that students possess a certain level of ability to interact with their course materials, analyze that interaction, and then write both about their interaction and analyses. However, limitations in working memory and Theory of Mind (ToM) create additional barriers for students with ASD in meeting these presumptions. Fortunately, emerging scholarly practices within the digital humanities (DH) now provide more equitable mediums for scholastic output as well as new opportunities for students to access and interact with course content and materials. While current structures within academia presuppose that students are able to interact with materials in a specific way, libraries are uniquely positioned to collaborate with constituent departments and services across campuses of higher education to teach students emerging strategies to more effectively interact with scholarly materials. Therefore, the focus of this article is twofold: it 1) considers how digital humanities techniques and methodologies increase accessibility to course materials and scholarship opportunities for students with Autism Spectrum Disorder; and 2) outlines how libraries can collaborate with existing services to provide subsequently appropriate supports for students to more effectively interact with their course materials. Autism Spectrum Disorder The 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) characterizes ASD as a range of neurodevelopmental conditions that manifest through either deficiency in social interaction and communication across multiple contexts, or restricted, repetitive patterns of behavior, interests, or activities3 . Since the publication of DSM-5 in 2013, ASD now “encompasses disorders previously referred to as early infantile autism, childhood autism, Kanner’s autism, high-functioning autism, atypical autism, pervasive developmental disorder not otherwise specified, childhood disintegrative disorder, and Asperger’s disorder.”4 Subsequently, the challenges that those with ASD face can vary depending on the manifestation in each individual. ASD continues to grow as one of the most common manifestations of neurodivergence both inside and outside of higher education. The Center for Disease Control and Prevention’s most recent statistics indicate that the overall prevalence of ASD is approximately 1 in 59 children over the age of 8 years old, or approximately 1.7% of the overall student population.5 Despite the increased prevalence and understanding of ASD, graduation rates within higher education for students with ASD remain low. According to a 2011 report commissioned by the US Department of Education, 52% of students without any registered disability graduate from their respective programs, while only 39% of students with ASD graduate.6 These statistics reveal a gap in equitable higher education opportunities for students with ASD. This gap becomes even more apparent when considering the number of students who enter higher education without a formal ASD diagnosis or who choose not to disclose their diagnosis. In a study conducted by White et al. evaluating the prevalence of students with ASD on college campuses, none of the 5 participants who met ASD criteria from the 667 sample set had previously been diagnosed.7 Furthermore, Underhill et al. discovered that many students elect not to disclose their diagnosis out of fear of either becoming stigmatized by their instructors and peers or creating new social barriers for themselves.8 Subsequently, these students do not receive many of their entitled supports, and it is likely that the true gap in graduation rates is larger than the statistics indicate. Supports prioritizing immediate social, environmental, and executive function challenges are increasingly becoming routine procedure across institutions of higher education. In order to effectively establish equitable learning environments for students with ASD, however, it is imperative that support be given to students in navigating the inherent social and communicative components of scholarship, especially within disciplines that emphasize expository and persuasive writing. Acknowledging these fundamental characteristics of traditional scholarship and the added challenges that they create for students with ASD will positively contribute to establishing more inclusive, equitable learning environments. Social and Communicative Characteristics of Traditional Scholarship The social and communicative interactions inherent within traditional modes of scholarship create barriers for students with ASD. Despite oral communication barriers appearing more immediate than those created by written language due to observable extrinsic manifestations, the skills required to understand and interpret both modes of communication remain similar. In fact, the syntactical structure and language of the written word is often more complex than oral speech.9 This can be especially true of the materials that students work with in higher education that, depending on the discipline, may incorporate high amounts of technical writing, figurative language, or older systems of speech that are no longer used in contemporary language. Language comprehension is established by forming inferences and hypotheses from the language used, the schemata in which it exists, and the context in which it was delivered. It presupposes an inherent understanding of the social constructs of language.10 In order to accurately and effectively make inferences based on the schemata and structure of the communicated information, one must have mastered the social context in which the information exists and is delivered. Current social skills interventions offered through therapy treatments can assist those with ASD to interpret facial expressions, body language, and other markers to better navigate social interactions.11 These strategies can be used to indicate when sarcasm, metaphor, or other nonliteral expressions of language may be changing the meaning of what is spoken.12 However, students do not have the same markers that help recognize such constructs when reading. In speaking of figurative language, Vuchanova et al. state that “such expressions are characterized by interpretations which cannot be retrieved by simply knowing basic senses of constituent lexical item, and where the addressee needs to arrive at the intended meaning rather than what is being said.”13 Therefore, while the skills required to understand oral and written language are similar, interpreting written language relies solely on the intrinsic social and communicative literacy of the reader, while oral language interpretation can benefit from extrinsic interventions. Producing written language, however, proves even more challenging than interpreting it. In a study on effective writing interventions for students with ASD, Accardo et al. state that “writing has a social context, follows rules and conventions, and makes use of inferences and ambiguous meaning to convey humor and metaphor, all of which can be challenging to individuals with ASD.”14 When reading, students only need to recognize the social context of what is presented, but when writing, they are expected to recreate that social context and use it to deliver their thoughts and findings. The skills needed to recognize social structures differ drastically from those needed to replicate these structures, and as such students with ASD face significant barriers in producing traditional scholarly outputs. Furthermore, the rules and conventions of writing differ depending on genre. In a 2020 study, Price et al. demonstrate that expository and persuasive writing prove more challenging than narrative writing for students with ASD.15 Additionally, Walters’ 2015 case study into the experiences of two first year writing students with ASD states that one student “struggled to translate her passion for writing into the classroom because her ways of writing – particularly in her fan fiction communities – were not valued as social or socially meaningful in her course.”16 Students in higher education are not only expected to write across genres, but also are often writing across academic disciplines that incorporate their own specific conventions. All of these challenges can be further understood by considering the roles of working memory and Theory of Mind in these processes. Working Memory Working memory proves essential for communicating any thoughts, ideas, or connections as it dictates the amount of information an individual can efficiently process at any given time. Camos and Barrouillet describe it “as a kind of mental space, located in frontal lobes of the brain, corresponding to a quick-access memory able to hold temporary, transient plans for guiding behavior.”17 It enables the multitasking functionality required when making connections, taking notes, and presenting information. Subsequently, students with ASD experience numerous challenges when interacting with their course materials due to limitations in their working memory. Thoughts easily get lost while considering the syntactical components and structure of language when performing tasks such as reading and writing. Graham et al. point to spelling as one such challenge. They state that “students may forget plans and ideas they are trying to hold in working memory as they stop to think about how to spell a word.”18 Similarly, thoughts and connections can be lost when attempting to parse the syntax and structure of complex writing, metaphors, figurative language, or other nonliteral structures. While executive function strategies, such as immediately writing down thoughts when you have them, are helpful techniques for overcoming such challenges, limitations in working memory present persistent obstacles for students with ASD. Theory of Mind ToM directly impacts how individuals recognize, empathize, and interact both with thoughts and emotions, and subsequently highlights many of the challenges that students with ASD face when interacting with their course materials. The role of ToM can be better understood by distinguishing between cognitive ToM and affective ToM. Pino et al. state that “cognitive ToM refers to the ability to make inferences about beliefs, intentions, motivations and thinking, whereas affective ToM is the ability to understand what people feel in specific emotional contexts such as their own emotional states.”19 In order to effectively make inferences and connections through cognitive ToM, it is necessary to recognize and understand emotional states and undertones through affective ToM. Scholarship, especially in the humanities, expects a high-level cognitive ToM, and subsequently, a strong foundation in affective ToM. However, the inherent social and communicative components of language and traditional scholarship create major barriers for students with ASD in establishing an affective ToM foundation. Limitations in working memory further exacerbate this loose foundation as students attempt to build upon it using the skills involved in cognitive ToM. Furthermore, studies demonstrate that students with ASD do not develop ToM skills at the same rate as their peers. ToM development progresses in a specific sequence, and Broekhof et al. demonstrate that while students with ASD follow the same sequence as their peers, their developmental timeline is comparatively delayed.20 In order to create equitable and inclusive learning environments in institutions of higher education, it is therefore essential that supports be implemented to assist students with ASD in overcoming these barriers and accessing course materials more effectively. Emerging Opportunities Over the last few decades, research and the way it is conducted has developed just as rapidly as the technology available to researchers. In reflecting upon research developments during this era of technological growth, it is easy to think about the way that new (and not so new) tools have been adopted into the research process. The digital humanities, however, encapsulates much more than just tools and how they can be integrated into humanities research. DH represents the discovery of new methodologies for doing research, new ways of interacting with materials, and new manners for telling stories and disseminating knowledge. DH is not a replacement for the humanities; it enlarges the scope of what is possible within the humanities and how humanities research can be done. It increases accessibility not only to how materials can be analyzed and interrogated, but also to how information can be shared and communicated. It allows for a much more inclusive environment that invites new perspectives and collaborations across disciplines. Not only do DH methodologies, techniques, and outputs grow the humanities, but they can also provide respite to many of the scholastic challenges that students with ASD face. These emerging scholarly practices create opportunities for people to access and interact with materials in ways that were previously not possible. Textual analysis techniques such as sentiment analyses and topic modeling can provide students with ASD opportunities to move beyond some of the challenges they face when interacting with course materials. Various forms of visualizations can provide alternative scholastic outputs for students instead of the more limiting traditional forms. DH practices can not only provide students with ASD the opportunity to interact with scholarly materials in a more unrestrained way, but they can also empower students to communicate their work and tell the stories they are interested in telling through a more unrestricted outlet. Furthermore, libraries have emerged as the center of DH support in institutions of higher education. This is due in part to libraries serving the needs of all constituent departments as a neutral entity. More importantly, however, libraries are devoted to helping students develop information literacy skills. The Association of College & Research Libraries’ (ACRL) Framework for Information Literacy in Higher Education (Framework) defines information literacy as “the set of integrated abilities encompassing the reflective discovery of information, the understanding of how information is produced and valued, and the use of information in creating new knowledge and participating ethically in communities of learning.”21) The values of information literacy and DH methodologies and practices ideally dovetail to make libraries the natural support structure for DH projects. Textual Analysis Strategies McKee describes a textual analysis as “a methodology – a data-gathering process – for those researchers who want to understand the ways in which members of various cultures and subcultures make sense of who they are, and of how they fit into the world in which they live.”22 Traditionally, researchers conduct such analyses by interrogating, interacting, and interpreting texts through close readings that combine their individual perspectives, contextual awareness, and the structures of the texts undergoing analysis. However, through DH practices the scope of what can be analyzed and how things are analyzed continues to grow larger. Individual words and the subsequent grammatical and syntactical structures in which they exist can now be analyzed as individual data points that allow increased accessibility to texts. Information hidden in the structure of the texts now can be mined, visualized, and interpreted. These practices do not replace traditional processes for gathering data from texts, instead they provide alternate access points for individuals to interact with the data, identify patterns and trends, and interpret the information presented. These alternative access points present students with ASD increased opportunity to interact with texts and bypass some of the social and communicative structures inherent within them. Idioms, similes, metaphors, and other representations of figurative language all base their comparisons on an intuited set of shared characteristics. Glucksburg claims that one technique for grasping the abstract meaning of figurative language is categorization, which “involves finding the nearest available category that subsumes both X and Y.”23 As previously discussed, connecting abstract concepts provides a barrier for students with ASD and consumes a large amount of their working memory. Topic modeling is a textual analysis strategy that simplifies this process by clustering similarly used words together to help illuminate the syntactical structure and schemata of the text. This allows students to more easily recognize patterns based on how the words are used within the local context, and focus on the meaning of those patterns instead of struggling to establish the syntactical structure of the text. Students are able to establish labels for these word clusters based on those patterns and assign their own meanings and interpretations to the groupings. The structures created by topic modeling allow students to move beyond the social and communicative schemata used to deliver the meaning, create a more solid affective ToM foundation, and maximize the amount of working memory available to interact with the meaning of a text though cognitive ToM skills. Students can also perform a sentiment analysis on a text as a strategy for moving beyond literal language. Sentiment analyses, or opinion mining, allow students to perform emotion recognitions and polarity detections to establish words or phrases in a text that represent emotional meanings. Emotion recognitions can not only help solidify an affective ToM foundation within the context of any given text, but they can also alleviate some challenges posed by limitations in working memory by providing a non-abstract structure for students to recognize and assign more figurative and abstract concepts. Similarly, polarity detection creates a structure in which abstract ideas can be categorized by emotional relation and be used comparatively. Cambria states that polarity detection is “usually a binary classification task with outputs such as ‘positive’ versus ‘negative,’ ‘thumbs up’ versus ‘thumbs down,’ or ‘like’ versus ‘dislike’.”24 Such identification can be especially useful in comparing voices within a single text or comparing tone within larger corpora. Similarly to topic modeling, sentiment analyses maximize students’ functional ability to employ cognitive ToM skills to interact with course materials beyond the meaning of the language within that set schemata. Strategies such as these relate directly to two of the threshold concepts in ACRL’s Framework: “Information has Value” and “Research as Inquiry”. First, ACRL states, “Information possesses several dimensions of value, including as a commodity, as a means of education, as a means to influence, and as a means of negotiating and understanding the world.”25 When interrogating texts, there are several layers of information and dimensions of value. Researchers can extract a plethora of information and insight conducting a close reading of a text. However, incorporating textual analysis strategies allows for different information and insight to be drawn from different layers of resources. These strategies increase the scope of what is possible when working with texts. Furthermore, ACRL adds that “research is iterative and depends upon asking increasingly complex or new questions whose answers in turn develop additional questions or lines of inquiry in any field.”26 These strategies allow researchers to ask questions and embark down roads of inquiry that were not possible in the past. In helping students develop information literacy skills, librarians encourage the use of new research strategies to find new ways of interacting and interpreting information encased within materials. Alternative Outputs Emerging DH methodologies not only allow for outputs, such as story mapping, geographic information system mapping, and social network analyses to be considered as alternatives to traditional forms of scholarship, but in some cases they necesitate it. As technological advancements grow and new methods of conducting research emerge, traditional forms of scholarship grow increasingly restrictive. Unilaterally relying on traditional scholarly outputs undermines the research process and places greater emphasis on individual outputs than on the research itself. Scholarly outputs are simply instruments used to communicate knowledge derived from the research process. To adhere to a singular, prescriptive output while more appropriate outputs exist for communicating specific information is not only counterintuitive, but also jeopardizes the impact of the research itself. In leading the charge to develop student’s information literacy skills, libraries emerge as ideal advocates for promoting the implementation of increased scholarly outputs. ACRL’s Framework cites “Information Creation as a Process” as one of the threshold concepts of information literacy. In defining this frame, ACRL states, “Information in any format is produced to convey a message and is shared via a selected delivery method.”27 It adds that “the iterative processes of researching, creating, revising, and disseminating information vary, and the resulting product reflects these differences.”28 In order to properly assist students in developing information literacy skills, it is therefore essential that librarians not only make students aware of alternative outputs, but that they also advocate to constituent departments on campuses of higher education to do the same. In order to create inclusive learning environments for students with ASD, the emphasis needs to be placed on the research process itself, not the output. Emphasizing traditional outputs highlights limitations beyond students’ control. In focusing emphasis on the research process, students will be empowered to direct their efforts to conducting research and developing strong foundational research strategies. It is imperative to encourage students to communicate their research through the medium that they perceive to be the appropriate output for their project or individual communication style. Opportunities for Library Supports Libraries provide an ideal infrastructure for supporting neurodivergent students to more effectively interact with scholarly materials. These supports need to take a more prominent role in conversations regarding the future of information literacy. As emerging scholarly practices continue to become an increasingly prominent part of research, it is important to consider the challenges that neurodivergent students face when interacting with materials, and consider new research techniques and methodologies as opportunities to create more accessible, inclusive learning environments. This endeavor is not only a cornerstone of information literacy, but a principal value of librarianship. In discussing the differences between data and information, Lanning asserts that information needs “some kind of context for their meaning to be discerned.”29 As discussed, there are numerous layers to this context that create barriers for neurodivergent students to effectively interact with information due to the social and communicative aspects of the syntactical schemata in which it exists, limitations in working memory, and comparatively delayed ToM development. However, the unique role of libraries within institutions of higher education creates opportunities to teach emerging research techniques and strategies to students directly, collaborate with services across campus to create more holistic support networks, and work directly with constituent campus departments to establish inclusive learning environments. Campus-wide Collaborations In a study into establishing strategies for more effectively integrating student supports into their academics, Dadger et al. found that all strategies have the same two aims: “(a) to make student services and supports a natural part of students’ college experience and (b) to increase the quality of both support services and instruction.”30 In order to effectively meet these goals with relation to supporting neurodivergent students and establishing a strong network of services, increased collaborations between librarians and disability services, academic mentors and coaches, and advising personnel are crucial. The challenges that neurodivergent students face are multifaceted and require a widespread system of supports that work harmoniously together. Dadger et al. found that the first step to creating such a network is to connect preexisting services.31 Many established library services, especially one-on-one consultations with librarians, can prove beneficial to neurodivergent students, but students may not be aware that these services exist. Students who disclose their diagnoses and seek supports from campus are involved in at least some, if not all, of the aforementioned programs, so increased collaborations can increase visibility of preexisting library services. Such collaborations would also invite the establishment of new supports. In a 2018 survey assessing which supports students with ASD found most helpful, Accardo et al. discovered that 91% of participants identified academic coaching as a preferred service, with one participant adding that coaching is a support that “isn’t contingent on somebody’s agenda for me.”32 Academic coaching and mentoring provides increased agency to students, and librarians can positively contribute to furthering that development by providing services around interacting with course materials. If greater collaboration exists between librarians and mentors, then mentors will both be able to suggest to their students specific library services that benefit their individual goals and plans, as well as make suggestions to librarians for new services that they think would benefit their students. All of these collaborations can help students interact with their course materials by making library services more visible and encouraging increased communication between students and their full network of supports. Liaising with Constituent Departments As previously discussed, many neurodivergent students elect not to disclose their diagnoses and subsequently do not receive any of the services to which they are entitled. This makes it all the more important for liaison librarians to work closely with their constituent departments to establish inclusive environments and practices. Much of the outreach that liaison librarians do is already geared towards creating inclusive learning environments, but it is imperative that liaison librarians bring new research strategies both to their students and faculty to ensure continued growth in developing such practices and spaces. As conversations focused on neurodivergent inclusivity within information literacy continue, many new practices will emerge and liaison librarians will be the primary drivers of delivering these practices across campuses. For now, many of these practices within the humanities are emerging through DH engagement, so it is imperative that liaison librarians focus on cultivating DH understanding and acceptance within the culture of their constituent departments. Organizing workshops and presentations that incorporate DH practices relevant to departmental research interests, inviting constituent faculty to collaborate on a project incorporating emerging scholarly practices, and sharing digital projects are a few examples of efforts that may lead to increased opportunities to grow emerging practices in constituent departments. Many disciplines are still in the midst of establishing best practices for considering scholarship and outputs that fall outside the traditional scope, and as such, may be unsure as to how to appropriately encourage students to engage with such practices. Moving forward, libraries will continue to play an integral role not only in supporting the creation of new information and scholarship, but also ensuring that best practices are created for using research innovation to create inclusive learning environments. Teaching Emerging Research Techniques The majority of students will engage with library-led information literacy opportunities through supplementary sessions within courses taught through constituent campus departments. While some courses may integrate these sessions at numerous points during a semester, it is common that students either only have the opportunity to participate in one session or are not presented with the opportunity at all. The focus of these content-oriented courses is not to develop information literacy skills for interacting with course materials, but instead is on extrapolating knowledge or ideas by interacting with the course material and then presenting this knowledge through a largely proscriptive medium. Their structures presuppose that students are able to interact with the materials in a specific way, and are not designed to teach students how to interact with the materials themselves. They may introduce new forms of materials and teach students how to use or incorporate those materials, but even within these situations the ability to interact with the information is assumed. While these courses may not be the appropriate place to teach students techniques or research methods that enable a deeper interaction with their texts, such a course is necessary. The mission and values of librarianship make libraries the ideal home for such courses. Libraries are becoming the central support for emerging scholarly practices and DH, and the devotion that librarians demonstrate to information literacy make them ideally suited not only to teach students how to interact with materials, but also how to present their work in nontraditional ways. Such courses can empower all students, but especially neurodivergent students, to not only take control of their own research endeavors but also to increase agency when participating in other courses. Despite most academic disciplines requiring some variation of a discipline-specific research and writing course, these courses are structured around traditional academic norms that do not provide neurodivergent students with the supports they need for effectively interacting with materials. If libraries begin offering courses that teach these supports, then neurodivergent students may face reduced barriers in their discipline-specific courses. More research into the effectiveness of such courses needs to be conducted, but indicators discussed in this article suggest that they have the potential to positively contribute to more inclusive learning environments. Conclusion Institutions of higher education are currently maneuvering shifts both in the neurological makeup of student populations and the composition of scholarship itself. As student populations continue to grow more neurodiverse, and DH practices establish themselves as research norms, libraries will play an important role in establishing more inclusive learning environments for students and faculty. Neurodivergent students face a plethora of additional challenges to their peers. While many of those challenges are already being supported through various services, there are no institutionalized supports that help students approach the social and communicative aspects of interacting with information and their course materials. Limitations in working memory and ToM development combined with the social and communicative components inherent within the engagement with and production of traditional modes of scholarship significantly impact neurodivergent students’ abilities to successfully maneuver collegiate expectations. However, libraries can play a decisive role in supporting these students and creating more inclusive learning environments. DH methodologies and practices challenge the limitations of traditional modes of scholarship and provide neurodivergent students an opportunity both to interact with and present information in ways that they were unable to in the past. Libraries can currently teach strategies for interacting with information by integrating into the ever-growing system of services campuses offer students. They can implement research strategy courses that specifically target the research needs of neurodivergent students and advocate for more inclusive practices to be implemented within constituent departments. Moving forward there is an increasing need for greater emphasis to be placed on supporting the information literacy needs of neurodivergent students. As institutions of higher education continue to grow more neurodiverse, it is the responsibility of libraries to create accessible means and strategies for students to effectively interact with and present information. Acknowledgements I would like to extend my sincerest gratitude to peer reviewers Jessica Schomberg and Bethany Redcliffe, as well as publishing editor Ian Beilin for their insight, enthusiasm, and encouragement throughout the review process. Their thoughtful feedback and probing questions contributed immensely to the formation of this article. I would also like to thank Merinda McLure, whose continued support and guidance during the early stages of developing these ideas was irreplaceable. I am very thankful for all of your efforts and contributions to making this the piece that it is. Thank you all! References Accardo, Amy L., Elizabeth G. Finnegan, S. Jay Kuder, and Estyr M. Bomgardner. “Writing Interventions for Individuals with Autism Spectrum Disorder: A Research Synthesis.” Journal of Autism and Developmental Disorders, March 5, 2019. https://doi.org/10.1007/s10803-019-03955-9. Accardo, Amy L., S Jay Kuder, and John Woodruff, “Accommodations and Support Services Preferred by College Students with Autism Spectrum Disorder.” Autism, February 23, 2018. https://doi.org/10.1177/1362361318760490. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (Arlington, VA: American Psychiatric Association, 2013). Anderson, Anastasia H., Jennifer Stephenson, and Mark Carter. “A Systematic Literature Review of the Experiences and Supports of Students with Autism Spectrum Disorder in Post-Secondary Education.” Research in Autism Spectrum Disorders 39 (July 2017): 33–53. https://doi.org/10.1016/j.rasd.2017.04.002. Association of College and Research Libraries (ACRL). “Framework for Information Literacy for Higher Education.” (2015) Barnhill, Gena P. “Supporting Students With Asperger Syndrome on College Campuses: Current Practices.” Focus on Autism and Other Developmental Disabilities 31, no. 1 (March 2016): 3–15. https://doi.org/10.1177/1088357614523121. Broekhof, Evelien, Lizet Ketelaar, Lex Stockmann, Annette van Zijp, Marieke G. N. Bos, and Carolien Rieffe. “The Understanding of Intentions, Desires and Beliefs in Young Children with Autism Spectrum Disorder.” Journal of Autism and Developmental Disorders 45, no. 7 (July 2015): 2035-2045. Cambria, E. “Affective Computing and Sentiment Analysis.” IEEE Intelligent Systems 31, no.2 (March 2016):102-107. Camos, Valerie and Pierre Barrouillet. Working Memory in Development (Abingdon, Oxon: Routledge, 2018). Centers for Disease Control and Prevention (2018) Prevalence of Autism Spectrum Disorder among Children Aged 8 Years. Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2014. Morbidity and Mortality Weekly Report (MMWR) Surveillance Summary, 67(6), 1–28. https://www.cdc.gov/mmwr/volumes/67/ss/pdfs/ss6706a1-H.pdf Dadgar, Mina, Thad Nodine, Kathy Reeves Bracco, and Andrea Venezia. “Strategies for Integrating Student Supports and Academics: Strategies for Integrating Student Supports and Academics,” New Directions for Community Colleges no. 167 (September 2014): 41–51. https://doi.org/10.1002/cc.20109. Fox, Jesse, and Jennifer J. Moreland. “The Dark Side of Social Networking Sites: An Exploration of the Relational and Psychological Stressors Associated with Facebook Use and Affordances.” Computers in Human Behavior 45 (April 2015): 168–76. https://doi.org/10.1016/j.chb.2014.11.083. Glucksberg, S. “Understanding Metaphors: the Paradox of Unlike Things Compared,” in Ahmad K. (eds) Affective Computing and Sentiment Analysis: Emotion, Metaphor, and Terminology. Springer, Dordrecht, 2011. Graham, Steve, Alyson A. Collins, and Hope Rigby-Wills. “Writing Characteristics of Students with Learning Disabilities and Typically Achieving Peers: A Meta-Analysis.” Exceptional Children 83, no. 2 (January 2017): 199–218. https://doi.org/10.1177/0014402916664070. Kamhi, Alan G. and Hugh W. Catts. “Language and Reading: Convergences, Divergences, and Development,” in Reading Disabilities. Boston, Massachusetts: College-Hill Press, 1989. Kross, Ethan, Philippe Verduyn, Emre Demiralp, Jiyoung Park, David Seungjae Lee, Natalie Lin, Holly Shablack, John Jonides, and Oscar Ybarra. “Facebook Use Predicts Declines in Subjective Well-Being in Young Adults.” PLOS ONE 8, no. 8 (August 14, 2013): e69841. https://doi.org/10.1371/journal.pone.0069841. Lanning, Scott. Concise Guide to Information Literacy, 2nd Edition. Santa Barbara, California, 2017. Lerner, Matthew D., and Amori Y. Mikami. “A Preliminary Randomized Controlled Trial of Two Social Skills Interventions for Youth With High-Functioning Autism Spectrum Disorders.” Focus on Autism and Other Developmental Disabilities 27, no. 3 (September 2012): 147–57. https://doi.org/10.1177/1088357612450613. Lin, Liu yi, Jaime E. Sidani, Ariel Shensa, Ana Radovic, Elizabeth Miller, Jason B. Colditz, Beth L. Hoffman, Leila M. Giles, and Brian A. Primack. “Association Between Social Media Use and Depression Among U.S. Young Adults: Research Article: Social Media and Depression.” Depression and Anxiety 33, no. 4 (April 2016): 323–31. https://doi.org/10.1002/da.22466. McKee, Alan. Textual Analysis : A Beginner’s Guide. London: SAGE Publications, 2003. ProQuest Ebook Central. Newman, L., Wagner, M., Knokey, A.-M., Marder, C., Nagle, K., Shaver, D., … Schwarting, M. (2011). The Post-high School Outcomes of Young Adults with Disabilities up to 8 Years after High School. A Report from the National Longitudinal Transition Study-2 (NLTS2) (NCSER 2011–3005) Menlo Park, CA: SRI International. Peterson, Candida C. and Henry M. Wellman. “Longitudinal Theory of Mind (ToM) Development from Preschool to Adolescence with and without ToM Delay.” Child Development 00, no.0 (April 2018): 1-18. https://doi.org/10.1111/cdev.13064. Pino, Maria Chiara, Monica Mazza, Maelania Mariano, Sara Peretti, Dagmara Dimitriou, Francesco Masedu, Marco Valenti, and Fabia Franco. “Simple Mindreading Abilities Predict Complex Theory of Mind: Developmental Delay in Autism Spectrum Diorders.” Journal of Autism and Developmental Disorders 47, no. 9 (September 2017): 2743-2756. Price, Johanna R., Gary E. Martin, Kong Chen, and Jennifer R. Jones. “A Preliminary Study of Writing Skills in Adolescents with Autism Across Persuasive, Expository, and Narrative Genres.” Journal of Autism and Developmental Disorders 50, no. 1 (January 2020): 319–32. https://doi.org/10.1007/s10803-019-04254-z. Twenge, Jean M., Thomas E. Joiner, Megan L. Rogers, and Gabrielle N. Martin. “Increases in Depressive Symptoms, Suicide-Related Outcomes, and Suicide Rates Among U.S. Adolescents After 2010 and Links to Increased New Media Screen Time.” Clinical Psychological Science 6, no. 1 (January 2018): 3–17. https://doi.org/10.1177/2167702617723376. Underhill, Jill Cornelius, Victoria Ledford, and Hillary Adams. “Autism Stigma in Communication Classrooms: Exploring Peer Attitudes and Motivations toward Interacting with Atypical Students.” Communication Education 68, no. 2 (April 3, 2019): 175–92. https://doi.org/10.1080/03634523.2019.1569247. Van Hees, Valérie, Tinneke Moyson, and Herbert Roeyers. “Higher Education Experiences of Students with Autism Spectrum Disorder: Challenges, Benefits and Support Needs.” Journal of Autism and Developmental Disorders 45, no. 6 (June 2015): 1673–88. https://doi.org/10.1007/s10803-014-2324-2. Vannucci, Anna, Kaitlin M. Flannery, and Christine McCauley Ohannessian. “Social Media Use and Anxiety in Emerging Adults.” Journal of Affective Disorders 207 (January 1, 2017): 163-166. Vulchanova, Mila, David Saldana, Sobh Chahboun, and Valentin Vulchanov. “Figurative Language Processing in Atypical Populations: The ASD Perspective.” Frontiers in Human Neuroscience 9 (February 17, 2015). https://doi.org/10.3389/fnhum.2015.00024. Walters, Shannon. “Toward a Critical ASD Pedagogy of Insight: Teaching, Researching, and Valuing the Social Literacies of Neurodiverse Students,” Research in the Teaching of English Vol. 49, No. 4 (May 2015): 340-360. White, Susan W., Thomas H. Ollendick, and Bethany C. Bray. “College Students on the Autism Spectrum: Prevalence and Associated Problems.” Autism 15, no. 6 (November 2011): 683–701. https://doi.org/10.1177/1362361310393363. Wei, Xin, Mary Wagner, Laura Hudson, Jennifer W. Yu, and Harold Javitz. “The Effect of Transition Planning Participation and Goal-Setting on College Enrollment Among Youth with Autism Spectrum Disorders.” Remedial and Special Education 37, no. 1 (January 2016): 3–14. https://doi.org/10.1177/0741932515581495. Fox et al., “The Dark Side of Social Networking Sites: An Exploration of the Relational and Psychological Stressors Associated with Facebook Use and Affordances.” Computers in Human Behavior 45 (2015): 168–76.; Kross et al., “Facebook Use Predicts Declines in Subjective Well-Being in Young Adults.” PLoS ONE 8, no. 8 (2013): 1-6.; Lin et al., “Association Between Social Media Use and Depression Among U.S. Young Adults: Research Article: Social Media and Depression.” Depression and Anxiety 33, no. 4 (2016): 323–31.; Twenge et al., “Increases in Depressive Symptoms, Suicide-Related Outcomes, and Suicide Rates Among U.S. Adolescents After 2010 and Links to Increased New Media Screen Time.” Clinical Psychological Science 6, no. 1 (2018): 3–17.; Vannucci et al., “Social Media Use and Anxiety in Emerging Adults.” Journal of Affective Disorders 207 (2017): 163-166. [↩] Accardo et al., “Accommodations and Support Services Preferred by College Students with Autism Spectrum Disorder.” Autism 23, no.3 (April 2019): 574.; Anderson et al., “A Systematic Literature Review of the Experiences and Supports of Students with Autism Spectrum Disorder in Post-Secondary Education.” Research in Autism Spectrum Disorders 39 (2017): 33–34.; Gena P. Barnhill, “Supporting Students with Asperger Syndrome on College Campuses: Current Practices.” Focus on Autism and Other Developmental Disabilities 31, no. 1 (2016): 3.; Underhill et al., “Autism Stigma in Communication Classrooms: Exploring Peer Attitudes and Motivations toward Interacting with Atypical Students.” Communication Education 68, no. 2 (2019): 175.; Van Hees et al., “Higher Education Experiences of Students with Autism Spectrum Disorder: Challenges, Benefits and Support Needs.” Journal of Autism and Developmental Disorders 45, no. 6 (2015): 1673.; Wei et al., “The Effect of Transition Planning Participation and Goal-Setting on College Enrollment Among Youth with Autism Spectrum Disorders.” Remedial and Special Education 37, no. 1 (2016): 3–14. [↩] American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (2013). [↩] Ibid. [↩] Centers for Disease Control and Prevention, Prevalence of autism spectrum disorder among children aged 8 years. Autism and developmental disabilities monitoring network, 11 Sites, United States, 2014 (2018): 2. [↩] Newman et al., The post-high school outcomes of young adults with disabilities up to 8 years after high school. A report from the National Longitudinal Transition Study-2 (NLTS2) (2011): 16-21. [↩] White et al., “College Students on the Autism Spectrum: Prevalence and Associated Problems,” Autism 15, no. 6 (2011): 695. [↩] Underhill et al., “Autism Stigma in Communication Classrooms: Exploring Peer Attitudes and Motivations toward Interacting with Atypical Students,” Communication Education 68, no. 2 (2019): 189-190. [↩] Alan G. Kamhi and Hugh W. Catts., “Language and Reading: Convergences, Divergences, and Development,” in Reading Disabilities (1989):1-34. [↩] Ibid. [↩] Matthew D. Lerner and Amori Y. Mikami., “A Preliminary Randomized Controlled Trial of Two Social Skills Interventions for Youth With High-Functioning Autism Spectrum Disorders.” Focus on Autism and Other Developmental Disabilities 27, no. 3 (2012): 147–57. [↩] It is important to remember here that there are multiple manifestations of ASD, and while these techniques can be modified to support individuals with ASD, they are not applicable universally and do not prove effective for all people. Furthermore, these techniques help recognize that something more may be contributing to what is being communicated beyond the literal meaning of the words, but they do not always help decipher the full meaning of what is being communicated. [↩] Vulchanova et al., “Figurative Language Processing in Atypical Populations: The ASD Perspective,” Frontiers in Human Neuroscience 9 (2015): 1. [↩] Accardo et al., “Writing Interventions for Individuals with Autism Spectrum Disorder: A Research Synthesis,” Journal of Autism and Developmental Disorders (2019): 2. [↩] Price et al., “A Preliminary Study of Writing Skills in Adolescents with Autism Across Persuasive, Expository, and Narrative Genres.” Journal of Autism and Developmental Disorders 50, no. 1 (2020): 319–32. [↩] Shannon Walters, “Toward a Critical ASD Pedagogy of Insight: Teaching, Researching, and Valuing the Social Literacies of Neurodiverse Students,” Research in the Teaching of English Vol. 49, No. 4 (May 2015): 353-354. [↩] Valerie Camos and Pierre Barroulillet, Working Memory in Development (2018): 3. [↩] Graham et al., “Writing Characteristics of Students with Learning Disabilities and Typically Achieving Peers: A Meta-Analysis,” Exceptional Children 83, no. 2 (2017): 200. [↩] Maria Chiara Pino et al., “Simple Mindreading Abilities Predict Complex Theory of Mind: Developmental Delay in Autism Spectrum Diorders.” Journal of Autism and Developmental Disorders 47, no. 9 (2017): 2744. [↩] Evelien Broekhof et al., “The Understanding of Intentions, Desires and Beliefs in Young Children with Autism Spectrum Disorder,” Journal of Autism and Developmental Disorders 45, no. 7 (2015): 2035-2045. [↩] Association of College and Research Libraries (ACRL). “Framework for Information Literacy for Higher Education.” (2015 [↩] Alan McKee, Textual Analysis : A Beginner’s Guide. (London: SAGE Publications, 2003), ProQuest Ebook Central: 8. [↩] S. Glucksberg, “Understanding Metaphors: the Paradox of Unlike Things Compared,” in Ahmad K. (eds), Affective computing and sentiment analysis: emotion, metaphor, and terminology, Springer, Dordrecht (2011): 4. [↩] E. Cambria, “Affective Computing and Sentiment Analysis,” IEEE Intelligent Systems 31, no.2 (March 2016):103. [↩] ACRL (2015). [↩] Ibid. [↩] Ibid. [↩] Ibid. [↩] Scott Lanning, Concise Guide to Information Literacy (2017): 3. [↩] Mina Dadgar et al.“Strategies for Integrating Student Supports and Academics: Strategies for Integrating Student Supports and Academics,” New Directions for Community Colleges no. 167 (2014): 50–51. [↩] Ibid, 48-49. [↩] Accardo et al. (2018), 574-83. [↩] Open to What? A Critical Evaluation of OER Efficacy Studies Multilingualism, Neoliberalism, and Language Ideologies in Libraries This work is licensed under a CC Attribution 4.0 License. ISSN 1944-6195. About this Journal | Archives | Submissions | Conduct