Student perceptions of teaching presence in an online academic reading module : an action research study

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY-NC 4.0 https://creativecommons.org/licenses/by-nc/4.0/ Student perceptions of teaching presence in an online academic reading module : an action research study © Authors and University of Jyväskylä 2024 Published version Orszag, Aaron Orszag, A. (2024). Student perceptions of teaching presence in an online academic reading module : an action research study. In A. Károly, L. Kokkonen, M. Gerlander, & P. Taalas (Eds.), Driving and embracing change : learning and teaching languages and communication in higher education (pp. 181-198). University of Jyväskylä. JYU Studies, 1. https://urn.fi/URN:ISBN:978952-86-0238-5 2024 Student perceptions of teaching presence in an online... 181 STUDENT PERCEPTIONS OF TEACHING PRESENCE IN AN ONLINE ACADEMIC READING MODULE An Action research study Aaron Orszag Understanding students’ perceptions of teaching presence in online learning environments is crucial for designing effective teaching. This action research project took place over four years with four different cohorts and examined how teaching presence, a key dimension of the Community of Inquiry (CoI) framework, was affected by three pedagogical factors: embedded support, learning environment layout, and teacher feedback against a base model. The study involved first-year bachelor’s students in education enrolled in a mandatory language course focusing on academic literacies. Embedded within this course was an e-learning module designed to develop students’ academic reading skills. The aim of the action research was to determine whether student perceptions of teaching presence significantly increased with the introduction of each of the pedagogical factors. The research also investigated how students’ confidence in their academic ability (CAA), confidence in English (CE), and working mode (WM, individual or group work) affected their perceptions of teaching presence in the module. Confirmatory factor analysis, measurement invariance, comparison of means, and regression analysis were used to test different variables. The results indicate that embedded support seems to be the most crucial pedagogical factor affecting students’ perceptions of teaching presence. There was no significant difference observed in the effect of students’ CAA, CE, and WM on their perception of teaching presence across all four cohorts. However, in the 2021 cohort, students who completed the e-learning module individually reported significantly higher perceived teaching presence than did those who worked in a group. These students appeared to form groups based on perceived CAA rather than selfrated CE, but this finding was not observed across the other three cohorts. The results highlight the impact of different pedagogical factors and student choices on teaching presence, which has important implications for designing effective online courses. Keywords: teaching presence, online learning, pedagogical design, academic reading, community of inquiry Orszag 182 Tehokkaan opetuksen suunnittelun kannalta on ratkaisevan tärkeää ymmärtää, miten opiskelijat havaitsevat opetuksellisen läsnäolon verkko-oppimisympäristöissä. Tässä nelivuotisessa ja neljän eri kohortin toimintatutkimushankkeessa selvitettiin, miten kolme pedagogista tekijää, eli integroitu tuki, oppimisympäristön järjestelyt ja opettajan antama palaute verrattuna perusmalliin, vaikuttivat opetukselliseen läsnäoloon, joka on keskeinen ulottuvuus tutkivan yhteisön (Community of Inquiry, CoI) mallissa. Tutkimukseen osallistui ensimmäisen vuoden kasvatustieteen kandidaattiopiskelijoita, jotka suorittivat pakollista akateemisten tekstitaitojen kurssia. Kurssiin sisältyi verkko-opetusmoduuli, jonka tarkoituksena oli kehittää opiskelijoiden akateemista lukutaitoa. Toimintatutkimuksen tavoitteena oli selvittää, lisäsikö kunkin pedagogisen tekijän käyttöönotto merkittävästi opiskelijoiden havaintoja opetuksellisesta läsnäolosta. Tutkimuksessa selvitettiin myös, miten opiskelijoiden luottamus akateemisiin kykyihinsä (CAA) ja englannin kielen taitoonsa (CE) sekä heidän käyttämänsä työskentelytapa (WM, yksilötai ryhmätyöskentely) vaikuttivat heidän havaintoihinsa opetuksellisesta läsnäolosta moduulissa. Muuttujia testattiin konfirmatorisen faktorianalyysin, mittausinvarianssin, keskiarvovertailun ja regressioanalyysin avulla. Tulokset osoittavat, että integroitu tuki näyttää olevan tärkein opiskelijoiden havaintoihin opetuksellisesta läsnäolosta vaikuttava tekijä. Minkään kohortin osalta ei todettu merkitsevää eroa opiskelijoiden CAA:n, CE:n ja WM:n vaikutuksessa heidän havaintoihinsa opetuksellisesta läsnäolosta. Vuoden 2021 kohortissa verkko-opetusmoduulin yksilöllisesti suorittaneet opiskelijat kuitenkin raportoivat havainneensa opetuksellista läsnäoloa huomattavasti enemmän kuin ryhmässä työskennelleet opiskelijat. Nämä opiskelijat näyttivät muodostavan ryhmiä pikemminkin koetun CAA:n kuin itsearvioidun CE:n perusteella, mutta tätä havaintoa ei tehty kolmessa muussa kohortissa. Tulokset tuovat esiin erilaisten pedagogisten tekijöiden ja opiskelijoiden valintojen vaikutukset opetukselliseen läsnäoloon, millä on merkittäviä implikaatioita toimivien verkkokurssien suunnitteluun. Asiasanat: opetuksellinen läsnäolo, verkko-opetus, pedagoginen suunnittelu, akateeminen lukeminen, tutkiva yhteisö Introduction The Community of Inquiry (CoI) is a prominent theoretical framework for designing and analysing online learning environments. According to this model, learning is facilitated through three factors: teaching, social, and cognitive presence (Garrison et al., 2010). Teaching presence is defined as the support of social and cognitive presences to achieve educational outcomes, social presence refers to the ability of learners to express their personalities and interact within a learning community, and cognitive presence is the ability of learners to construct meaning through dialogue (Garrison et al., 2010). It is important to note that presence does not refer to physical presence but to an individual being perceived as there to help or guide (Song et al., 2019). Combining these two definitions one can define teaching presence as students’ perceptions of the pedagogical design of the course to support their social and cognitive development. Of the three presences, teaching presence plays a central role in the CoI because it supports the other two presences (Domenech-Betoret et al., 2017; Shen et al., 2013). According to Garrison (2017), teaching presence is based on design and Student perceptions of teaching presence in an online... 183 organisation, facilitation, and direct instruction. Design and organisation are the structure and logical progression of the course, facilitation provides meaning and understanding for each individual student, and direct instruction refers to correcting misconceptions and providing timely academic expertise for the students. Despite the assumed significance of teaching presence in the CoI, further research is needed to explore this concept in different contexts, including the use of assessment and student perceptions of teaching presence (Garrison, 2017). Some researchers have proposed that a fourth dimension, learning presence, should be added to the CoI (Ma et al., 2017; Shea et al., 2014). Learning presence is defined as the behaviour, motivation, emotions, and strategies for successful learning (Shea & Bidjerano, 2012). However, this distinction between teaching and learning presence would compromise the basic principles that the CoI was founded on (Garrison, 2017). This debate suggests that further research into teaching presence is needed. A review of the recent literature indicates that the research focuses on verifying the use of CoI in different contexts and modifying and validating different items and constructs rather than on comparing how groups of students differ in terms of context, institutional setting, major, or stage of studies. Two studies (Ma et al., 2017; Wertz, 2022) found that learning presence and teaching presence were separate constructs. Ma et al. (2017) found that teaching and social presence influenced learning presence, while Wertz (2022) only mentions that learning presence should be added to the CoI. Neither study analysed how different groups viewed the CoI even though they had the chance to compare institutions, years at university, and major. Two studies (Heilporn & Lakhal, 2020; Wertz, 2022) found that a two-variable construct of teaching presence consisting of course design and facilitation was best because facilitation and direct instruction were highly correlated. Heilporn and Lakhal (2020) collected data from two universities and found them invariant, which means that the two groups viewed the questionnaire’s questions the same. However, they did not conduct a comparison of means (e.g., t test, ANOVA) on the two universities. One study by Lau et al. (2021) compared gender and major with teaching presence and found no significant difference between these factors, but they did not test for invariance. Heilporn and Lakhal (2020) have called for more multi-group analysis on the CoI which tests for invariance and could provide researchers and teachers with a better understanding of teaching presence. This action research, conducted over four years, aims to investigate how different pedagogical factors, embedded support, learning environment layout, and teacher feedback affect student perceptions of teaching presence in an online academic reading module. An additional aim was to investigate whether working mode (group or individual work), confidence in academic ability, and confidence in English affect teaching presence. E-learning Design Course background The English language e-learning module at the centre of this study focused on reading an academic article written in English. It was part of a compulsory multilingual academic literacy course taught in Finnish, English, and Swedish at the University of Jyväskylä, which was also integrated with the students’ home department course. As a learning environment, the academic literacy course used Moodle 3.5 for the 2018 cohort and Moodle 3.9.7 for the 2021 cohort, with the e-learning module embedded into the Moodle workspace. The Orszag 184 students had one month to complete the e-learning module, but they were able to request more time. Base design: Cohort 2018 The base model of the e-learning module was designed in such a way that the students had the choice to work either in a group or individually. The teacher encouraged students who were less confident in their English skills or their academic ability to work in a group. The teacher introduced the module, explained how long it would take, and gave the students the option to skip certain activities. Cho and Heron (2015) pointed out that if a course is too structured, competent learners will feel a lack of control and therefore experience dissatisfaction. The module consisted of mini-learning modules (MLM) focusing on the following: identifying academic articles, finding key information in an academic article, and paraphrasing and summarising. Each MLM was based on the cyclical phases in Zimmerman’s (2013) framework of self-regulated learning (SRL): forethought, performance, and self-reflection. SRL is defined as an individual’s active use of metacognition, motivation, and behaviour in their learning (Zimmerman, 1989, 2008). Garrison and Arkyol (2015) suggested that since the CoI makes the students reflect, process, and reflect again, it offers a good model for promoting SRL. Zimmerman (2013) also distinguished two types of learners, proactive and reactive. Proactive learners use more forethought than reactive learners, who, in turn, use selfreflection after a performance to learn. This means that proactive learners are goal-oriented and more confident in their learning due to a perceived similar experience and thus are able to use more self-regulation in their learning. Proactive learners also have high self-efficacy (Zimmerman, 2013). In contrast, reactive learners tend to have lower self-efficacy because of not having had a perceived similar experience and thus would use self-reflection to increase their selfefficacy/self-regulation in the future. Therefore, they would need observations and emulation activities with the help of social interaction from the teacher or other students. Cho et al. (2017) highlight that understanding and developing learners’ self-regulation would have a positive effect on teaching presence. In the course, performance activities were all mandatory assignments, and the selfreflection activities were only available after the students completed the performance activity. The self-reflection activities were designed following a multimodal approach, allowing students to reflect on their answers through a written text or a video with teacher comments. All the material was designed using the Cognitive Affective Theory of Learning with Media (Moreno & Mayer, 2007). No feedback was given to the students during these MLMs except after the final summary. This was done because too much teacher support has been shown to restrict students’ metacognition (Larkin, 2009). It was also assumed that assessing every single performance activity would be unsustainable for the teacher. The CoI teaching presence questionnaire was integrated into the e-learning module after the final summary and data were collected before teacher feedback on the final summary to ensure a high response rate and to see how students perceive teaching presence without teacher feedback. Embedded support: Cohort 2019 Based on students’ feedback and analysis of the data from the CoI questionnaire from the 2018 cohort, embedded support was added. This support first meant labelling the SRL Student perceptions of teaching presence in an online... 185 cyclical phases as think (forethought), act (performance), and check (self-reflection). According to Lim et al. (2020), it is important for students to be aware of their learning to succeed at university. It was assumed that these labels would help students better understand the SRL process and their own learning. Second, support videos were added. These were think-aloud videos by the teacher to demonstrate academic reading strategies. Neebe (2017) found that such think-aloud videos increased students’ attention to strategies and helped them continue when faced with a challenging task. The videos also provided observation opportunities for students, which is the first phase in SRL and can lead to a higher sense of self-efficacy (Ahm et al., 2017; Zimmerman, 2013). Finally, videos can also increase teacher credibility and persuasion power (Won et al., 2017). In the videos, the teacher demonstrated the process of academic reading, using an academic article written in a language the teacher did not know well (Swedish). It was assumed that if the teacher had a similar learning experience as the students, this would increase the teacher’s credibility and demonstrate that a student can also complete the task. Third, an overview video of the e-learning module was added to the beginning of the module to help students understand the goals and completion methods of the e-learning module. In the previous year, the e-learning module was only explained in the first class of the course but not in the module. Fourth, an example of a summary (an authentic text written by a student in a similar course) was added with teacher comments in the text. Alternatively, students could watch a video of the teacher analysing and evaluating the summary. The last addition was face-to-face support for students who wanted it. As in the previous year, the questionnaire was integrated into the e-learning module at the end, and data were collected before teacher feedback on the final summary. Learning environment layout: Cohort 2020 For the 2020 cohort, the layout of the e-learning module was changed. Instead of showing all the activities in Moodle, they were hidden from the students but linked to in a course outline table with suggested deadlines also showing links to register for face-to-face teacher support in Zoom. These deadlines were not mandatory but were intended to give students a time frame for completing the e-learning module. The data were collected the same way as in the previous two years to enable the researcher to see how course layout as a single factor influenced teaching presence. This was also the first time running the e-learning module during the COVID-19 pandemic. Teacher feedback: Cohort 2021 For the 2021 cohort, face-to-face support was dropped as no student was using it, but students were encouraged to email the teacher with their questions. The data for this year were collected after teacher feedback on the final summary to analyse if the feedback had an impact on teaching presence. Orszag 186 Methods Participants The participants were first-year students at a Finnish university, studying in a Finnishlanguage education BA program. Out of 608 students enrolled in the course over four years, 282 students participated in the study by completing the survey, which means a response rate of 46.38%. See Table 1 for the yearly and total response rate. Table 1 Yearly and Total Response Rate Cohort Number of students completing the module Number of students completing the survey Response rate (%) 2018 119 80 67.2 2019 161 84 52.1 2020 173 69 39.8 2021 155 49 31.61 Total 608 282 46.38 Data collection methods The CoI questionnaire based on the Community of Inquiry Survey Instrument (draft v14 (n.d.) was reverse translated from English into Finnish and then back to English by professional translators to ensure an accurate Finnish translation. Only the first two dimensions of the CoI questionnaire – design and organisation along with facilitation – were used in this study to measure teaching presence. There were ten items altogether, four for design and organisation, labelled tp1–tp4 and six for facilitation, labelled tp5–tp10. The students rated these items on a Likert scale from 1 to 5 with 1 being strongly disagree to 5 being strongly agree. In addition to measuring teaching presence, the independent variables were cohort, confidence in academic ability (CAA) as well as confidence in English (CE) – both labelled as not confident or confident and then converted to 1 for not confident and 2 for confident – and working mode (individual or group), which was converted to 1 for individual and 2 for group. CAA and CE were not collected for the second year. Data analysis The data were analysed in RStudio (2022.07.1 build 554) running R 4.2.1. To conduct a confirmatory factor analysis (CFA), a sufficiently large sample size is needed. According to Wolf et al. (2016), the sample size is based on latent variables, items, and loadings. The more latent variables a study has, the larger the sample size. However, using a higher number of items and a higher loading of those items on the latent variables allows for using a lower sample size. Based on Wolf et al.’s (2016) research, a minimum sample size of two latent variables with 10 indicators would require a sample size of 160 for a loading of .50, 130 for a loading of .65, and 90 for a loading of .8. Wertz (2022) used the same two latent factors as this Student perceptions of teaching presence in an online... 187 study and had loadings from .69 to .88 to indicate that 90 to 130 participants were needed to conduct a similar CFA. According to Maydeu-Olivares (2017), before conducting a CFA one has to determine if the data is normal or nonnormal. After this step, there are many estimators that a researcher can use to conduct a CFA (Maydeu-Olivares, 2017). The estimators ML or MLF can be used for normally distributed data and MLM, MLMV, and MLR for non-normal distribution. To determine the goodness of fit for the CFA model, a model should be above 0.95 for CFI and TLI and below 0.08 for RMSEA and 0.06 for SRMR (Hu and Bentler, 1999). However, Levesque et al. (2004) suggested that an RMSEA of 0.05 or less is a very good fit and that an RMSEA between 0.05 and 0.08 is a reasonable fit. A test of measurement invariance (MI) for cohort, confidence in English, confidence in academic ability, and the working mode was conducted. MI tests a construct across groups to ensure that the different groups interpret the items the same. It consists of three tests: configural, metric, and scalar invariance. According to Putnick and Bornstein (2016), once these tests have been passed, even with partial scalar invariance, one can compare the group means of latent factors. They also emphasised that when testing MI, there is no consensus on the best-fit indices or cutoff values. They mentioned that a significance in χ2 is traditionally used, but now most researchers use the criterion of a –.01 change in CFI. This study used the -.01 change in CFI. MI groups were then tested using a combination of one-way ANOVA, Turkey’s HSD, and t tests. Regression analysis was also used to test if confidence in English and confidence in academic ability affected the choice of working mode. Finally, Moodle statistical data on click counts for teaching feedback and “check activities” was collected to see if students were reading teacher feedback and clicking on the check activities. Results Descriptive statistics All the items had an increase in their means over all four years. However, from 2019 to 2020 there was a lower mean for the indicator tp1 in design and organisation, as well as in all the facilitation indicators. This was also the first time the e-learning module was conducted during the COVID-19 pandemic. All the indicators were higher in 2021. (See Table 2 for an overview of the individual means of each indicator per year.) Most of the students (77%) completed the e-learning module individually, with only 23% completing the module as a group over the four years. However, in the 2021 cohort, 55% completed the module as a group, and 45% did it individually. It is also important to note that not all the students in the overall population clicked on the check activities. On average, 89% of the students clicked on the check activities. What is more interesting is that on average only 35% of the overall population of the students checked the teacher’s feedback. See Table 3 for more detailed information by year, the working mode, the percentage of students who clicked on the check activities and looked at teacher feedback. Orszag 188 Table 2 Item Means and SD for Each Cohort 2018 2019 2020 2021 tp1 3.29 (1.03) 3.85 (0.92) 3.72 (0.97) 3.80 (0.93) tp2 3.22 (0.97) 3.76 (0.89) 3.78 (0.94) 3.82 (0.86) tp3 2.84 (1.13) 3.67 (0.91) 3.77 (0.93) 3.84 (0.90) tp4 3.28 (1.26) 3.93 (0.85) 4.39 (0.75) 4.47 (0.65) tp5 2.59 (0.98) 3.06 (0.88) 3.00 (0.97) 3.29 (0.98) tp6 2.96 (1.00) 3.57 (0.92) 3.33 (0.89) 3.53 (1.02) tp7 3.01 (1.20) 3.44 (1.03) 3.19 (0.96) 3.37 (1.00) tp8 3.00 (1.06) 3.38 (0.97) 3.29 (0.88) 3.59 (0.84) tp9 3.21 (1.12) 3.58 (1.02) 3.32 (1.02) 3.63 (1.03) tp10 3.08 (1.12) 3.48 (1.07) 3.04 (1.02) 3.59 (1.00) Table 3 Percentages of Work Mode, Clicked-on Check Activity, and Checked Teacher Feedback 2018 2019 2020 2021 Working modea Group N (%) 16 (20) 12 (14) 9 (13) 27 (55) Individual N (%) 64 (80) 72 (86) 60 (87) 22 (45) Clicked on check activity (%)b PDF/Video 1 No data collected 80 76 No data collected PDF/Video 2 93 89 PDF/Video 2 93 88 PDF/Video 4 100 95 Checked teacher feedback (%)cNo data collected 30 45 30 a Percentage is calculated by the individuals who responded to the questionnaire. b Percentage is calculated in Moodle with the overall population. These percentages are just estimates and include both teacher and students who viewed the text/video. c Percentage is calculated in Moodle by the Turnitin activity and calculated with the overall population that completed the final assignment. Marida’s test Marida’s test was tested on items tp1–tp10 to see if the data was normal or non-normal. The test resulted in a skewness of p = 0.00 and a kurtosis of p = 0.00, which indicates that the data is non-normal, and a robust or non-normal distribution estimator should be used. The MLM estimator was decided on because the data were complete. Confirmatory factor analysis The validity of the instrument was tested with confirmatory factor analysis (CFA) in two stages using the MLM estimator. The first CFA using a two-factor model with design and Student perceptions of teaching presence in an online... 195 information in the available literature on the CoI in terms of whether the main assignments/ tasks were done in groups, individually, or mixed for each study. Although the CoI encourages community, there seems to be a lack of information on whether participants are contributing to the overall course community individually or working with a pair/group first before contributing to the overall community. Many studies combined different courses with the brief comment that teaching methods were similar. As shown in this study, however, working in a group or individually might influence perceptions of teaching presence. A systematic or meta-analysis review of group work and teacher feedback on teaching presence would provide deeper insights into this aspect. 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Author Aaron Orszag, University Teacher, Centre for Multilingual Academic Communication, University of Jyväskylä, ORCID ID: 0000-0001-5462-5389 Aaron Orszag is University Teacher at the Centre for Multilingual Academic Communication at the University of Jyväskylä. He is interested in online collaborative learning, critical thinking, active learning and student agency, and issues of equitable grading and assessment.