15
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Comparing the writing skills of autistic and nonautistic university students: A collaboration with autistic university students

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The writing skills of autistic university students have received very little empirical attention. Previous research has suggested that autistic people may struggle with writing, in part, due to challenges with Theory of Mind. However, other research indicates that Theory of Mind difficulties are far from universal in autism, varying across developmental and social contexts. Through a participatory research approach, autistic university students contributed to the current study examining the writing strengths and challenges of autistic ( n = 25) and nonautistic ( n = 25) university students. Autistic participants demonstrated more advanced writing skills, more perfectionistic attitudes about writing, and heightened nonverbal intelligence relative to nonautistic students. Autistic students did not exhibit reduced Theory of Mind skills. Although heightened nonverbal intelligence and being autistic were both initially predictive of writing quality, autism was no longer associated with writing quality after accounting for nonverbal intelligence. Findings suggest that autistic university students may often have enhanced cognitive and writing skills but may face challenges overcoming perfectionism. This research highlights the value of participatory collaborations with autistic students for identifying strengths that can help autistic students succeed in college.

          Lay abstract

          We do not know very much about the writing skills of autistic university students. Studies with autistic children and teenagers show that some autistic young people have difficulties writing. Other autistic people are talented writers. In fact, some autistic people would rather write than speak. Good writers often imagine other people’s points of view when writing. Autistic people sometimes have difficulties understanding others’ points of view. Yet, autistic people often work much harder to understand others’ points of view than not-autistic people do. We collaborated with autistic university student researchers to see if autistic university students are better or worse at writing than nonautistic students. Autistic university students in our study were better writers than nonautistic students. Autistic students in our study had higher nonverbal intelligence than nonautistic students. Autistic students also put themselves under more pressure to write perfectly than nonautistic students did. Autistic students did not show any difficulties understanding other minds. This study shows that some autistic university students have stronger writing skills and higher intelligence than nonautistic university students. Yet, autistic students may be too hard on themselves about their writing. Fun activities that help students explore their ideas without pressure (like theater games) may help autistic students be less hard on their writing. Teachers can help autistic students express themselves through writing by encouraging them to write about their interests, by giving them enough time to write, and by letting them write using computers if they want to. This study shows that collaborations with autistic people can help us understand strengths that can help autistic people succeed.

          Related collections

          Most cited references63

          • Record: found
          • Abstract: found
          • Article: not found

          Effect size, confidence interval and statistical significance: a practical guide for biologists.

          Null hypothesis significance testing (NHST) is the dominant statistical approach in biology, although it has many, frequently unappreciated, problems. Most importantly, NHST does not provide us with two crucial pieces of information: (1) the magnitude of an effect of interest, and (2) the precision of the estimate of the magnitude of that effect. All biologists should be ultimately interested in biological importance, which may be assessed using the magnitude of an effect, but not its statistical significance. Therefore, we advocate presentation of measures of the magnitude of effects (i.e. effect size statistics) and their confidence intervals (CIs) in all biological journals. Combined use of an effect size and its CIs enables one to assess the relationships within data more effectively than the use of p values, regardless of statistical significance. In addition, routine presentation of effect sizes will encourage researchers to view their results in the context of previous research and facilitate the incorporation of results into future meta-analysis, which has been increasingly used as the standard method of quantitative review in biology. In this article, we extensively discuss two dimensionless (and thus standardised) classes of effect size statistics: d statistics (standardised mean difference) and r statistics (correlation coefficient), because these can be calculated from almost all study designs and also because their calculations are essential for meta-analysis. However, our focus on these standardised effect size statistics does not mean unstandardised effect size statistics (e.g. mean difference and regression coefficient) are less important. We provide potential solutions for four main technical problems researchers may encounter when calculating effect size and CIs: (1) when covariates exist, (2) when bias in estimating effect size is possible, (3) when data have non-normal error structure and/or variances, and (4) when data are non-independent. Although interpretations of effect sizes are often difficult, we provide some pointers to help researchers. This paper serves both as a beginner's instruction manual and a stimulus for changing statistical practice for the better in the biological sciences.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Bayesian inference for psychology. Part II: Example applications with JASP

            Bayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the need to know the intention with which the data were collected. Despite these and other practical advantages, Bayesian hypothesis tests are still reported relatively rarely. An important impediment to the widespread adoption of Bayesian tests is arguably the lack of user-friendly software for the run-of-the-mill statistical problems that confront psychologists for the analysis of almost every experiment: the t-test, ANOVA, correlation, regression, and contingency tables. In Part II of this series we introduce JASP (http://www.jasp-stats.org), an open-source, cross-platform, user-friendly graphical software package that allows users to carry out Bayesian hypothesis tests for standard statistical problems. JASP is based in part on the Bayesian analyses implemented in Morey and Rouder’s BayesFactor package for R. Armed with JASP, the practical advantages of Bayesian hypothesis testing are only a mouse click away.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              On the ontological status of autism: the ‘double empathy problem’

                Bookmark

                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Autism
                Autism
                SAGE Publications
                1362-3613
                1461-7005
                July 08 2020
                : 136236132092945
                Affiliations
                [1 ]The City University of New York, USA
                [2 ]University of California, Davis, USA
                [3 ]University of Virginia, USA
                [4 ]Fairleigh Dickinson University, USA
                Article
                10.1177/1362361320929453
                32640841
                e4025821-9728-414d-b730-888251161350
                © 2020

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

                History

                Comments

                Comment on this article