Background: Research incorporating large data sets and data and text mining methodologies is making initial contributions to writing studies. In writing program administration (WPA) work, one could best characterize the body of publications as small but growing, led by such work as Moxley and Eubanks’ 2015 “On Keeping Score: Instructors' vs. Students' Rubric Ratings of 46,689 Essays” and Arizona State University’s Science of Learning & Educational Technology (SoLET) Lab. Given the information that large-scale textual analysis can provide, it seems incumbent on program administrators to explore ways to make regular and aggressive use of such opportunities to give both students and instructors more resources for learning and development. This project is one attempt to add to this corpus of work; the sample for the study consisted of 17,534 pieces of student writing representing 141,659 discrete comments on that writing, with 58,300 unique words out of over 8.25 million total words written. This data is used to examine trends in the program’s instructor commentary over five years’ time.  By doing so, this study revisits a fundamental task of writing instruction—responding to student writing, and from the data’s results considers how large writing programs with constant turnover of graduate teaching assistants (GTAs) might manage their ongoing instructor professional development and how those GTAs will improve their ability to teach and respond to writing.Literature Review: Researchers have attempted to unpack and understand the task of instructor commentary for several decades; the published literature demonstrates a complex and occasionally ambivalent relationship with this central task of writing instruction. Recent scholarship has moved from the small-scale studies long used by the field to implement large-scale examinations of the instruction occurring in writing programs. Research questions: Three questions guided the inquiry:Does the work of new instructors (MA1s) more closely resemble the lexicon of novice or experienced responders to student writing?How does the new instructors’ work compare to that of more experienced (PHD1 or INS) instructors in the program throughout their time?How does their work evolve over a four-semester longitudinal time frame (as MA1 or MA2 experience levels) in the first-year writing program? [Please note that the abbreviations used above and throughout the article to designate instructor experience levels are as follows: MA1 (first-year master’s students); MA2 (second-year master’s students); PHD1 (first-year doctoral students); INS (instructors—those with 3 or more years’ experience teaching and who are not currently pursuing an additional degree—nearly all of these individuals held a Master’s degree)].Methodology: This study extends the work of Anson and Anson (2017) who first surveyed writing instructors and program administrators to create wordlists that survey respondents associated with “high-quality” and “novice” responses, and then examined a corpus of nearly 50,000 peer responses produced at a single university to learn to what extent instructors and student peers adopted this lexicon. Specifically, the study analyzes a corpus of instructor comments to students using the Anson and Anson wordlists associated with principled and novice commentary to see if new writing instructors align more closely with the concepts represented in either list during their first semester in the program.  It then tracks four cohorts for evolution and change in their vocabulary of feedback over their next three semesters in the program; the study also compares the vocabulary used in their comments to that used by experienced instructors in the program over the same time.Results: The study found that from the outset, the new instructors (MA1) incorporated more of the principled response terms than the novice response terms. Overall, in comparing the MA1 instructors with the most experienced group (INS), the results reveal three important findings about the feedback of both MA1s and INSs in this program.While there are some differences in commentary as seen via examination of the two lexicons, the differences are perhaps less than one might assume.The cohorts do increase their use of the principled terms as they move through the two years’ appointment in the program, but few of the increases demonstrate statistical significance.Few of the terms from either the novice or principled lexicon, with the exception of terms that also appear in the assignment descriptions, what I label as “content terms,” appear frequently in the overall corpus.Discussion: Based on the results, the instructors in this program had acquired a more consistent vocabulary, but not primarily one based on Anson and Anson’s two lexicons—instead, the most frequent and commonly used terms seem to come from a more local “canon,” that is, one based on the assignment descriptions and course outcomes. Regardless of whether the acquisition of a common vocabulary came from more global concepts or an assignment-based local canon, using common terms is something that Nancy Sommers (1982) saw as contributing to “thoughtful commentary” on student writing. As no one has previously studied how quickly new instructors acquire a professional vocabulary for responding to student writing, it is hard to know whether or not the results of this particular group of instructors would be considered “typical.” However, it may well be that the context of this writing program contributed to a more accelerated acquisition.Conclusions: Working with the lexicons developed via Anson and Anson’s survey is a useful starting point for understanding more of what our instructors actually do when responding to student writing, as well as for identifying critical differences in our instructors’ comments. The lexicons, though, only provide us with a subset of expected (thus acceptable) terms included in commentary—terms that afford students the opportunity to act upon receiving them via revision or transfer. Directions for Future Research: Additional research is necessary to expand and refine the lexicons and their impact on student writing. One possibility is to return to the current data set to engage in additional lexical analysis of both the novice and principled lexicons as well as the overall frequency tables to understand how terms are used in the context of response by the various instructor groups. Differences in the application of the terms might help us understand why comments might be labeled as more or less helpful to writers.  Another strategy is to examine the data in terms of markers of stance; finally, topic modeling could be used to locate more subtle differences in the instructor comments that are not as easily identifiable with lexical analysis. Such examinations could serve as a baseline for broadening the study out to other sets of assignments and commentary, perhaps helping us build a set of threshold concepts for talking about writing with our students. Ultimately, it is important to replicate and expand Anson and Anson’s survey to other stakeholder groups. As with much research on the teaching of writing, we default to the group most accessible to us—other writing professionals. Replicating this survey with other stakeholders—graduate teaching assistants, undergraduate students at both lower and upper division levels— could help us understand whether or not a gap exists in understanding what constitutes good feedback from the various stakeholders.

Background: Current research in composition and writing studies is concerned with issues of writing program evaluation and how writing tasks and their sequences scaffold students toward learning outcomes. These issues are beginning to be addressed by writing analytics research, which can be useful for identifying recurring types of language in writing assignments and how those can inform task design and student outcomes. To address these issues, this study provides a three-step method of sequencing, comparison, and diagnosis to understand how specific writing tasks fit into a classroom sequence as well as compare to larger genres of writing outside of the immediate writing classroom environment. By doing so, we provide writing program administrators with tools for describing what skills students demonstrate in a sequence of writing tasks and diagnosing how these skills match with writing students will do in later contexts. Literature Review: Student writing that responds to classroom assignments can be understood as genres, insofar as they are constructed responses that exist in similar rhetorical situations and perform similar social actions. Previous work in corpus analysis has looked at these genres, which helps us as writing instructors understand what kind of constructed responses are required of students and to make those expectations explicit. Aull (2017) examined a corpus of first-year undergraduate writing assignments in two courses to create “sociocognitive profiles” of these assignments. We analyze student writing that responds to similar writing tasks, but use a different corpus method that allows us to understand the tasks in both local and global contexts. By doing so, we gain confidence and depth in our understanding of these tasks, analyze how they sequence together, and are able to compare argumentative writing across institutions and contexts. Research Questions: Two questions guided our study: What is the trajectory of skills targeted by the sequence of tasks in the two first-year writing courses, as evidenced by the rhetorical strategies employed by the writers in successive assignments? Focusing on the final argument assignments, how similar are they to argumentative writing in other contexts, in terms of rhetorical profiles? Methodology: We first conducted a local analysis, in which we used a dictionary-based corpus method to analyze the rhetorical strategies used by writers in the first-year writing courses to understand how they built on each other to form a sequence. Having understood what skills students are demonstrating in a course, we then conducted a global analysis which calculated a “distance” between the first-year argument writing and a corpus of argument writing drawn from other contexts. Recognizing that there was a non-trivial distance, we then identified and evaluated the sources of the distance so that the writing tasks could be assessed or modified. Results: The local analysis revealed eight key rhetorical strategies that student writing exhibits between the two first-year writing courses. With this understanding, we then placed the argument writing in global contexts to find that the assignments in both courses differ somewhat from argument writing in other contexts. Upon analyzing this difference, we found that the first-year writing primarily differs in its usage of academic language, the personal register, assertive language, and reasoning. We suggest that these differences stem primarily from the rhetorical situation and learning objectives associated with first-year writing, as well as the sequencing of the courses. Discussion: The three-step method presented provides a means for writing program administrators to describe and analyze writing that students produce in their writing programs. We intend these steps to be understood as an iterative process, whereby writing programs can use these results to evaluate what rhetorical skills their students are exhibiting and to benchmark those against the program’s goals and/or other similar writing programs. Conclusions: By presenting these analyses together, we ultimately provide a cohesive method by which to analyze a writing program and benchmark students’ use of rhetorical strategies in relation to other argumentative contexts. We believe this method to be useful not only to individual writing programs, but to assessment literature broadly. In future research, we anticipate learning how this process will practically feed back into pedagogy, as well as understanding what placing writing tasks into a global context can tell us about genre theory.

Background: The researchers conducted a corpus analysis of 548 research-based argument essays, totalling 1,465,091 words, written by first-year students at The City College of New York (CCNY). The purpose of this study was to better understand the ways in which CCNY students were constructing arguments in research essays in order to better support our instruction of the research essay. Curricular guidelines for the research assignment are general. Instructors are directed to require a research-based, persuasive argument that includes conflicting points of view. Model assignment sheets are provided to instructors, but they are free to write their own. Assignment sheets are not collected or approved. In the fall semester in which this corpus was collected, over 70 part-time instructors taught approximately 120 sections of the first- or second-semester composition course.Literature Review: The study of The City College of New York Corpus (CCNYC) partially replicates and relies on the analysis of three corpora of academic writing conducted by Zak Lancaster (2016a) in his examination of Gerald Graff’s and Cathy Birkenstein’s textbook They Say/I Say: The Moves that Matter in Academic Writing (2014). The current study also compares the CCNYC findings to studies of stance and voice markers frequency conducted by Ken Hyland (2012) and Ellen Barton (1993) and suggests the classroom use of corpus analysis as described by Raith Abid and Shakila Manan (2015), and Maggie Charles (2007).Research Questions: The study was guided by a narrowly-focused interest in learning whether or not the CCNYC would demonstrate the range and distribution of rhetorical moves that Lancaster found in his study of academic writing (2016a). The analysis of the corpus consists of frequency counts; we did not conduct other statistical analyses. Since we had little prior experience with corpus analysis, we wondered what would be revealed about students’ writing practices by a partial replication of Lancaster’s study. We did not reproduce Lancaster’s analysis but relied on his publised results. This study served as an assessment tool, providing a microscopic view of a limited number of rhetorical moves across a large corpus of student essays. As a result of our study, we hoped to be able to create assignments for research essays that responded directly to the patterns that we saw in our students’ essays.Methodology: Modeled on Lancaster’s study and the templates of rhetorical moves offered by Graff and Birkenstein, concordances of terms used to introduce objections, offer concessions, and make counterarguments were drawn from the CCNYC and then analyzed to confirm that the rhetorical form was in fact functioning as one of the above rhetorical moves within the context of the essay in which it was found.Results: Our study demonstrates that CCNY students use fewer linguistic resources than their peers at other institutions, a finding that helps shape faculty development seminars. The corpus analysis reveals that while CCNY students introduce objections to their arguments at about the same rates as in other corpora, they are less likely to concede to those objections. In addition, when students made counterarguments, they used only a limited range of the linguistic resources available to them.Conclusions: The low rate of engagement with opposing points of view and the limited use of linguistic resources for counterarguments all suggest the potential value of focused, corpus-based instruction.

• Background: Researchers have been working towards better understanding differences in professional disciplinary writing (e.g., Ewer & Latorre, 1969; Hu & Cao, 2015; Hyland, 2002; Hyland & Tse, 2007) for decades. Recently, research has taken important steps towards understanding disciplinary variation in student writing. Much of this research is corpus-based and focuses on lexico-grammatical features in student writing as captured in the British Academic Written English (BAWE) corpus and the Michigan Corpus of Upper-level Student Papers (MICUSP). The present study extends this work by analyzing lexical and cohesion differences among disciplines in MICUSP. Critically, we analyze not only linguistic differences in macro-disciplines (science and engineering), but also in micro-disciplines within these macro-disciplines (biology, physics, industrial engineering, and mechanical engineering).\n• Literature Review: Hardy and Römer (2013) used a multidimensional analysis to investigate linguistic differences across four macro-disciplines represented in MICUSP. Durrant (2014, in press) analyzed vocabulary in texts produced by student writers in the BAWE corpus by discipline and level (year) and disciplinary differences in lexical bundles. Ward (2007) examined lexical differences within micro-disciplines of a single discipline.\n• Research Questions: The research questions that guide this study are as follows:\n1. Are there significant lexical and cohesive differences between science and engineering student writing? 2. Are there significant lexical and cohesive differences between micro-disciplines within science and engineering student writing?\n• Research Methodology: To address the research questions, student-produced science and engineering texts from MICUSP were analyzed with regard to lexical sophistication and textual features of cohesion. Specifically, 22 indices of lexical sophistication calculated by the Tool for the Automatic Analysis of Lexical Sophistication (TAALES; Kyle & Crossley, 2015) and 38 cohesion indices calculated by the Tool for the Automatic Analysis of Cohesion (TAACO; Crossley, Kyle, & McNamara, 2016) were used. These features were then compared both across science and engineering texts (addressing Research Question 1) and across micro-disciplines within science and engineering (biology and physics, industrial and mechanical engineering) using discriminate function analyses (DFA).\n• Results: The DFAs revealed significant linguistic differences, not only between student writing in the two macro-disciplines but also between the micro-disciplines. Differences in classification accuracy based on students’ years of study hovered at about 10%. An analysis of accuracies of classification by paper type found they were similar for larger and smaller sample sizes, providing some indication that paper type was not a confounding variable in classification accuracy.\n• Discussion: The findings provide strong support that macro-disciplinary and micro-disciplinary differences exist in student writing in these MICUSP samples and that these differences are likely not related to student level or paper type. These findings have important implications for understanding disciplinary differences. First, they confirm previous research that found the vocabulary used by different macro-disciplines to be “strikingly diverse” (Durrant, 2015), but they also show a remarkable diversity of cohesion features. The findings suggest that the common understanding of the STEM disciplines as “close” bears reconsideration in linguistic terms. Second, the lexical and cohesion differences between micro-disciplines are large enough and consistent enough to suggest that each micro-discipline can be thought of as containing a unique linguistic profile of features. Third, the differences discerned in the NLP analysis are evident at least as early as the final year of undergraduate study, suggesting that students at this level already have a solid understanding of the conventions of the disciplines of which they are aspiring to be members. Moreover, the differences are relatively homogeneous across levels, which confirms findings by Durrant (2015) but, importantly, extends these findings to include cohesion markers.\n• Conclusions: The findings from this study provide evidence that macro-disciplinary and micro-disciplinary differences at the linguistic level exist in student writing, not only in lexical use but also in text cohesion. A number of pedagogical applications of writing analytics are proposed based on the reported findings from TAALES and TAACO. Further studies using different corpora (e.g., BAWE) or purpose assembled corpora are suggested to address limitations in the size and range of text types found within MICUSP. This study also points the way toward studies of disciplinary differences using NLP approaches that capture data which goes beyond the lexical and cohesive features of text, including the use of part-of-speech tags, syntactic parsing, indices related to syntactic complexity and similarity, rhetorical features, or more advanced cohesion metrics (latent semantic analysis, latent Dirichlet allocation, Word2Vec approaches).

Aim: The screencast (SC), a 21st century analytics tool, enables the simultaneous recording of audio and video feedback on any digital document, image, or website, and may be used to enhance feedback systems in many educational settings. Although previous findings show that students and teachers have had positive experiences with recorded commentary, this method is still rarely used by teachers in composition classrooms. There are many possible reasons for this, some of which include the accelerated pace at which classroom technology has changed over the past decade, concerns over privacy when new technologies are integrated into the classroom, and the general unease instructors may feel when asked to integrate a new technology system into their established composition pedagogy and response routine. The aim of this study was to replicate previous findings in favor of SC feedback and expand that body of research beyond instructor-to-student SC interactions and into the realm of SC-mediated peer review. Thus, this study seeks to improve on the widespread written peer review practices most common among writing instruction today, practices that tend to produce mediocre learning outcomes and fail to capitalize on 21st century technological innovations to enhance student learning. This research note demonstrates the validity of SC as a valuable writing analytics research tool that has the potential to collect and measure student learning. It also seeks to inspire those who have been reluctant to adopt SC in both digital learning and face-to-face educational environments by providing pragmatic guidance for doing so in ways that simultaneously increase student learning and facilitate a more rigorous and discursive peer-to-peer review process. Problem Formation: While research suggests positive student perceptions related to screencast instructor response, results in peer-to-peer screencast response are mixed. After several successful years of experience in instructor-to-student SC feedback, the author wondered what would happen if she asked students to use screencast technology to mediate peer review. How might students’ attitudes and perceptions impact the use of peer-to-peer screencast technology in the composition classroom? In order to address these questions, the author developed a survey measuring the user reliability of this new SC technology and the student affect and revision initiative it produces. Information Collection: This study extends Anson’s (2016) research and insights by reporting findings from a study of 138 writing students. Survey data was collected during the 2015-2016 academic year at three institutions. At High Point University, the author of this research note asked freshmen composition students in a traditional face-to-face lecture course to conduct a series of peer review sessions (including both traditional written comments and SC comments) over a 16-week semester. Students were surveyed after each peer review experience, and the results form the foundation of this research note’s conclusions. In addition to survey responses, researchers also collected the screencasts exchanged among peer-to-peer interactions within each educational setting. Conclusions: The author provides an in-depth analysis of students’ experiences, perceptions, and attitudes toward giving and receiving screencast feedback, focusing on the impact of this method on student revision initiative in comparison to that of a traditional written feedback system. Some conclusions are also drawn regarding the user reliability and effectiveness of the screencast technology, specifically the free software program known as Jing, a product available through Techsmith.com that enables a streamlined and user-friendly SC interface and cloud storage of all SC recordings through individualized hyperlinks, thereby alleviating concerns regarding student privacy. Directions for Further Research: While this research note provides compelling evidence to support the use of SC in composition classrooms, there are also many opportunities for continued study, particularly within the emerging field of writing analytics. While the actual student-to-student screencasts were collected in this study, they were not analyzed as a qualitative data set, and the researchers relied on self-reported survey data to assess the degree of revision initiative among the students surveyed. The screencasts themselves offer a treasure trove of data, should the researcher have the capability to code that data set or utilize automated natural language processing programs in the future. Perhaps this peer-to-peer SC feedback could be compared to similar corpus analyses of instructor-to-student feedback gathered by other writing analytics scholars. In addition, further research in this area could also collect the student writing itself and track revisions made by students after receiving SC feedback and traditional written feedback from their peers. In this way, researchers would be able to make comparisons between the actual changes made by the student writers, the extent of those changes (surface-level or higher-order revisions), and the student’s perceived degree of revision initiative reported in the survey. To facilitate future research in this area, the author has included teaching resources for those new to screencast technology and analytics.

Background: Contemporary research in composition studies emphasizes the constitutive power of genres. It also highlights the prevalence of the most common genre in students’ transition into advanced college writing, the argumentative essay. Consistent with most research in composition, and therefore most studies of general, first-year college writing, such research has primarily emphasized genre context. Other research, in international applied linguistics research and particularly English for Academic Purposes (EAP), has focused less on first-year writers but has likewise shown the frequent use of argumentative essays in undergraduate writing. Together, these studies suggest that the argumentative essay is represented more than other genres in early college writing development, and that any given genre favors particular discourse features in contrast with other genres students might write. A productive next step, but one not yet realized, is to bring these discussions together, in research that uses context-informed corpus analysis that investigates students’ assignment contexts and analyzes the discourse that characterizes the tasks and genres students write. This study offers an exploratory, context-informed analysis of argumentative and explanatory writing by first-year college writers. Based on the corpus findings, the article underscores discourse as an integral part of the sociocognitive practices embedded in genres, and accordingly considers new ways to conceptualize student writing genres and to inform instruction and assignment design. Research questions: Four questions guided the inquiry: What are the key discursive practices associated with annotated bibliographies and argumentative essays written by the same students in the same course? What are the key discursive practices associated with visual analyses and argumentative essays written by the same students in the same course? What are the key discursive practices associated with the two argumentative tasks in comparison with the two explanatory tasks? Finally, how might corpus-based findings inform the design of particular assignment tasks and genres in light of a range of writing goals? Methodology: The article outlines a context-informed corpus analysis of lexical and grammatical keywords in part-of-speech tagged writing by first-year college students across courses at a U.S. institution. Using information from assignment descriptions and rubrics, the study considers four projects that also represent two macro-genres: an annotated bibliography and a visual analysis, both part of the explanatory macro-genre, and two argumentative essays, both part of the argumentative macro-genre. Results: The corpus analysis identifies lexical and grammatical keywords in each of the four tasks as well as in the macro-genres of argumentative versus explanatory writing. These include generalized, interpersonal, and persuasive discourse in argumentative essays versus more specified, informational, and elaborated discourse in explanatory writing, regardless of course or task. Based on these findings, the article discusses the discursive practices prioritized in each task and each macro-genre. Conclusions: The findings, based on key discourse patterns in tasks within the same course and in macro-genres across courses, pose important questions regarding writing task design and students’ adaptation to different genres. The macro-genre keywords specifically inform exploratory sociocognitive “profiles” of argumentative and explanatory tasks, offered in the final section. These argument and explanation profiles strive to account for discourse patterns, genre networks, and purposes and processes—in other words, multiple aspects of habituated thinking and writing practices entailed in each one relative to the other. As discussed in the conclusion, the profiles aim to (1) underscore discourse patterns as integral to the work of genres, (2) highlight adaptive discourse strategies as part of students’ meta-language for writing, and (3) identify multiple, macro-level (e.g., audience), meso-level (paragraph- and section-level), and micro-level (e.g., discourse patterns) aspects of genres to help instructors identify and specify multiple goals for writing assignments.

Background: Attention Deficit Hyperactivity Disorder (ADHD) is a mental health disorder. People diagnosed with ADHD are often inattentive (have difficulty focusing on a task for a considerable period), overly impulsive (make rash decisions), and are hyperactive (move excessively, often at inappropriate times). ADHD is often diagnosed through psychiatric assessments with additional input from physical/neurological evaluations. Written Language Disorder (WLD) is a learning disorder. People diagnosed with WLD often make multiple spelling, grammar, and punctuation mistakes, have sentences that lack cohesion and topic flow, and have trouble completing written assignments. Typically, WLD is also diagnosed through psychological educational assessments with additional input from physical/neurological evaluation. Literature Review: Previous research has shown a link between ADHD and writing difficulties. Students with ADHD have an increased likelihood of having writing difficulties, and rarely is there a presence of writing difficulties without ADHD or another mental health disorder. However, the presence of writing difficulties does not necessarily indicate the presence of a WLD. There are other physical and behavioral factors of ADHD that can contribute to a student having a WLD as well. Therefore, a statistical association between these factors (in conjunction with written performance) and WLD must first be established. Research Question: To determine the statistical association between WLD and physical and behavioral aspects of ADHD that indicate writing difficulties, this research reviewed methodologies from the literature pertaining to contemporary diagnoses of writing difficulties in ADHD students, and reveal diagnostic methods that explicitly associate the presence of WLD with these writing difficulties among students with ADHD. The results demonstrate the association between writing difficulties and WLD as it pertains to ADHD students using an integrated computational model employed on data from a systematic review. These results will be validated in a future study that will employ the integrated computational model to measure WLD among students with ADHD. Methodology: To measure the association of WLD among students with ADHD, the authors created a novel computational model that integrates the outcomes of common screening methods for WLD (physical questionnaire, behavioral questionnaire, and written performance tasks) with common screening methods for ADHD (physical questionnaire, behavioral questionnaire, adult self-reporting scales, and reaction-based continuous performance tasks (CPTs)). The outcomes of these screening methods were fed into an artificial neural network (ANN ) first, to ‘artificially learn’ about measuring the prevalence of WLD among ADHD students and second, to adjust the prevalence value based on information from different screening methods. This can be considered as the priming of the ANN. The ANN model was then tested with data from previous studies about ADHD students who had writing difficulties. The ANN model was also tested with data from students without ADHD or WLD, to serve as control. Results: The results show that physical, behavioral, and written performance attributes of ADHD students have a high correlation with WLD (r = 0.72 to 0.80) in comparison to control students (r = 0.30 to 0.20), substantiating the link between WLD and ADHD. It should be noted that due to lack of female participation, most studies in the literature only employed and reported on the relationship between WLD and ADHD for male participants. Discussion and Conclusion: By testing ADHD students and control students against the WLD criteria, the study shows a strong correlation between WLD and ADHD. There are limitations to the results’ accuracy in terms of a) sample size (average n=88, mean age = 19, 8 studies used for a meta-analysis), b) analysis (original study reviewing ADHD factors first, WLD factors second), and c) causation (the study only reviews prevalence of WLD in ADHD students, not causation). A clinical trial will validate the data and address some of these limitations in a future phase of the research. A computational causal model will be introduced in the discussion portion to illustrate how causation between writing metrics and WLD as it pertains to ADHD can be achieved. These results open the door to advancing pedagogical techniques in education, where students afflicted with ADHD and/or WLD could not only receive assistance for the behavioral aspects of their disorder, but also expect assistance for the learning aspects of their disorder, empowering them to succeed in their studies.