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      Factors underlying students’ attitudes towards multimodal collaborative writing

      research-article
      Heliyon
      Elsevier
      Attitudes, Multimodal, Digital literacy, Traditional writing

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          Abstract

          While multimodal writing is widely recognized as an effective way to increase engagement and motivation, its benefit also depends on the students’ attitudes. This study investigated students’ attitudes to a multimodal collaborative writing project and the factors affecting students’ attitudes. A total of 52 students selected using convenience sampling responded to a student survey that collected data about the perceived helpfulness of multimodal writing, teacher feedback, grade, ease, familiarity, and team member participation. Individual interviews with 11 students were also conducted to ascertain students’ opinions about the challenges and benefits of the multimodal collaborative writing project. The results indicated that factors related to information and research literacy, conventional writing, enablers and barriers played a primordial role in shaping students’ attitudes. Interestingly, many students appreciated multimodal writing for the benefits it has on their information and research literacy skills rather than on traditional writing skills. The study contributes to the body of knowledge on multimodal collaborative writing. However, there are some limitations that should be addressed in future research.

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          Most cited references27

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          Sample size in factor analysis.

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            Exploratory Factor Analysis With Small Sample Sizes.

            Exploratory factor analysis (EFA) is generally regarded as a technique for large sample sizes (N), with N = 50 as a reasonable absolute minimum. This study offers a comprehensive overview of the conditions in which EFA can yield good quality results for N below 50. Simulations were carried out to estimate the minimum required N for different levels of loadings (λ), number of factors (f), and number of variables (p) and to examine the extent to which a small N solution can sustain the presence of small distortions such as interfactor correlations, model error, secondary loadings, unequal loadings, and unequal p/f. Factor recovery was assessed in terms of pattern congruence coefficients, factor score correlations, Heywood cases, and the gap size between eigenvalues. A subsampling study was also conducted on a psychological dataset of individuals who filled in a Big Five Inventory via the Internet. Results showed that when data are well conditioned (i.e., high λ, low f, high p), EFA can yield reliable results for N well below 50, even in the presence of small distortions. Such conditions may be uncommon but should certainly not be ruled out in behavioral research data. ∗ These authors contributed equally to this work.
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              Is More Ever Too Much? The Number of Indicators per Factor in Confirmatory Factor Analysis.

              We evaluated whether "more is ever too much" for the number of indicators (p) per factor (p/f) in confirmatory factor analysis by varying sample size (N = 50-1000) and p/f (2-12 items per factor) in 35,000 Monte Carlo solutions. For all N's, solution behavior steadily improved (more proper solutions, more accurate parameter estimates, greater reliability) with increasing p/f. There was a compensatory relation between N and p/f: large p/f compensated for small N and large N compensated for small p/f, but large-N and large-p/f was best. A bias in the behavior of the χ(2) was also demonstrated where apparent goodness of fit declined with increasing p/f ratios even though approximating models were "true". Fit was similar for proper and improper solutions, as were parameter estimates form improper solutions not involving offending estimates. We also used the 12-p/f data to construct 2, 3, 4, or 6 parcels of items (e.g., two parcels of 6 items per factor, three parcels of 4 items per factor, etc.), but the 12-indicator (nonparceled) solutions were somewhat better behaved. At least for conditions in our simulation study, traditional "rules" implying fewer indicators should be used for smaller N may be inappropriate and researchers should consider using more indicators per factor that is evident in current practice.
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                Author and article information

                Contributors
                Journal
                Heliyon
                Heliyon
                Heliyon
                Elsevier
                2405-8440
                30 December 2022
                January 2023
                30 December 2022
                : 9
                : 1
                : e12725
                Affiliations
                [1]General Education Program, Rabdan Academy, Abu Dhabi, United Arab Emirates
                Article
                S2405-8440(22)04013-0 e12725
                10.1016/j.heliyon.2022.e12725
                9849981
                5ecc1bda-4674-4df9-894a-343ed8a6c860
                © 2022 The Author

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 5 May 2022
                : 17 November 2022
                : 26 December 2022
                Categories
                Research Article

                attitudes,multimodal,digital literacy,traditional writing

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