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Journal of Content, Community & CommunicationAmity School of CommunicationVol. 13 Year 7, June - 2021 [ISSN: 2395-7514 (Print) ]Amity University, Madhya Pradesh [ISSN: 2456-9011 (Online)]MEASURING THE WALLS OF COMMUNICATION BARRIERS OF STUDENTSIN HIGHER EDUCATION DURING ONLINE CLASSESDr. Geetanjali ShrivastavaAssistant Professor, Department of Commerce,The Bhopal School of Social Sciences, BhopalCorresponding Author - Email: geetanjalirudra9@gmail.comDr. Durdana OvaisAssistant Professor, Department of Commerce,The Bhopal School of Social Sciences, BhopalNeelakshi AroraAssistant Professor, Department of Commerce,The Bhopal School of Social Sciences, BhopalABSTRACTPurpose: The present research aims to evaluate the influence of online classes on higher educationstudents' achievement and the communication barriers they encountered while attending the classes.The study's constructs were online learning vs. offline learning, communication barriers, and effectivelearning outcomes.Design/ Methodology/Approach: The research study explores the relationship between theconstructs through an exploratory descriptive research design. The present research study collecteddata through structured questionnaires using established scales. The data was collected throughgoogle form from UG and PG students. G* power was used to analyse the required sample size forthe study. Data analysis was undertaken through SmartPLS software using SEM for analysing thestructural model of the study and to test the hypothesis.Findings: The study high though we live in the modern age and that our students are technologicallyadvanced, but still learning online is daunting. Students have a high preference for offline classesthan online classes. They were confronted with a variety of communication barriers (both verbal andnonverbal), including personal, physical, psychological, and emotional barriers. According tostudents, a teacher's physical presence is needed for a better understanding of the topics. It isunrealistic for them to absorb the entire syllabi of each subject in virtual mode, so they choose offlineclasses. Personal analytical abilities and speech skills, they believe, have also deteriorated in onlineclasses.Practical Implications: The findings suggested that more Faculty Learning programs should beinitiated to up-skill educators, as well as, more hands-on training should be provided for newsoftware. Students' feedback should be recorded on a daily basis to check the effectiveness of onlineclasses, and an asynchronous and synchronous learning mechanism should be set up for two-waycommunication between the students and the teachers.Originality Value: The research would undoubtedly assist in identifying the communication barriersthat students face in online classes, as well as paving the way for new approaches to make onlineclasses more effective for learning.Keywords: Online Classes, Offline Classes, Communication Barriers, Effective Learning, COVID-19.INTRODUCTIONCommunication is a basic requirement of life;we have been communicating ourselves sincebirth.Everyindividualcommunicatesuniquely, and the addition of technology hasmade it much easier and more convenient.There are unique barriers that hinder people'sability to articulate themselves. The primaryDOI: 10.31620/JCCC.06.21/22aim of this research is to identifycommunication barriers in higher educationstudents' online classes and to evaluate theeffectiveness of online lectures on theirlearning outcomes.The rise of online learning is not only fuelledby modern forms of communication, but the263

Pandemic has also given students acompelling reason to do so. Covid-19 hasmade a significant shift in the style of teachingand learning.voiced their concerns over the need for onlinestudents to be disciplined as well as lowerretention rates, suggesting that online learningwould not be sufficient for all students.Before Covid-19, though we had an onlineclass system, but it was more limited to distantonline courses or MOOCs like SWAYAM,COURSERA, and others. During thepandemic, when it was mandatory forstudents to attend online classes, it was foundthat students were not deeply interested inthem. Even those who are more interested inphysical classes did not seem to be as involvedand active in the online class mode. Thisresearch aims to identify the roadblocks thatdiscourage students from attending lectures.This study aims to know about students'perceptions toward online classes and toevaluate their degree of tolerance of bothonline and offline modes.(Abu, Kiramat, & Xu, 2020) in their work “Theeffect of communication barriers on distancelearners’ achievements” has postulated thatcommunication barriers such as social ogical barriers, psychological barriers,contextual barriers, and collaborative barriersare the significant challenge in distanceeducation, impacting the success andachievements of distance learners. Suchproblems also overlap and increase thecomplexity and anxiety of distance learners,impacting the success and achievements ofdistance learners.(Aynur, Tülay, & Zülfiye, 2015) in theirresearch on Communication Barriers in OnlineTeaching and Online Learning with DigitalMedia, in the Framework of Teaching andLearning Theory Approaches suggested thattheconventionalin-classteachingenvironment is favoured by learners becauseof the social nature of human beings and thetraditional educational environment oflearners. Teachers and other fellow learnersare involved in this environment and face-toface interaction can take place. It was observedthat both learners and teachers seem to be inneed of observing the gestures and behavior ofthe other. Moreover, for both teachers andlearners, technological and cultural challengesare likely to remain troubling.Importance of the Problem and Rationale forthe StudyThe students taking online courses or takingonline classes have risen exponentially andwill continue to rise. This is attributable notonly to the pandemic but also to the fact thatstudents have a variety of online platforms tochoose from for different classes. Thegovernment provides several E-learningplatforms and resources, but as we look atstudent preferences or learning outcomes, wefind that there are very different perspectives.This research aims to learn about students'attitudes toward online classes, as well as thechallenges they encounter, their expectations,and what new can be done in this field.(Muilenburg & Berge, 2005) in their work onStudent Barriers to Online Learning: A FactorAnalytic Study, highlighted eight factors: (a)administrative problems, (b) social interaction,(c) academic skills, (d) technical skills, (e)motivation of learners, (f) study time andsupport, (g) internet costs and connectivity,and (h) technical issues. The most significantbarrier to students studying online wasthe lack of social interaction, the findings werethat social interaction is closely linked tosatisfaction of online learning, online learningeffectiveness, and the chances of attendinganother online class. It seems obvious,therefore, that enhancing social interaction inonline learning will lead to a more successfuland enjoyable learning experience thatstudents would like to repeat.There is a limited amount of research thatoffers a comprehensive and scientificexamination of the communication barriersthat higher education students confront inonline courses. This research aims torecognize the challenges that students faceand their effectiveness as assessed bylearning outcomes, as well as to makerecommendations for enhancing the onlinelearning environment.LITERATURE REVIEW(Monkhouse, 1992) research showed theperspectives of Chief Academic Officers inorder to find answers to fundamentalquestions regarding Massive Open OnlineCourses (MOOCs). Academic leaders have264

(Abramenka, 2015) projected students concernover the barriers of online and hybridenvironments. Engagement and cooperation,communication with the instructor andcollaboration with peers, as well as confusinglayout, were reported by them.considerations. Higher education institutionsneed to provide professional development forinstructors, training for learners, and technicalassistance for curriculum development inorder to overcome these issues in the area ofonline education.(Kaushal Kumar Bhagat, Leon Yufeng Wu, &Chun-Yen Chang ,2016) focussed thatinstructors have multiple roles, ranging fromthe delivery of meaningful learning to thestudents' active involvement. The socialpresence will help educational developers tomaintain the standard of the online learningexperience, student-centred course design isincluded in the educational design element,which would inspire students to engage inonline learning environments(Khanna & Prasad, 2020) the study findingsshowed that most of the people faced internetchallenges and did not have the knowledge touse and solve technology-related issues.“There is a propensity to exhibit overtradingby retail investors in the state of fear of noinvestmentknowledgeandlackofconvenience due to news in smartphones,”(Shiva, Narula, & Shahi, 2020) stated in theirresearch. (Gilitwala & Nag, 2020) highlightedthat users' confidence, perceived usefulness,confirmation, perceived risk, and satisfactionwith the product or service all influenced theirintention to use near field communication inthe future.(Dabaj,2011)highlightedthatthecommunication barriers of distance learningare the physical distance between members,the challenges in coping with new media, timeconstraints and restrictions, prior experienceof distance learning, incompetence of technicalabilities, and the extent of interactivity level.Put all together, the method of successfuldistance education becomes almost difficult. Indifferent organizations and with differentdelivery systems used, the levels of thesebarriers are different.(Marks, Sibley, & Arbaugh, 2005) in theirstudy on “A Structural Equation Model ofPredictors for Effective Online Learning”highlighted that the interaction betweenteacher and student is most important,doubling to that, the interaction betweenstudent and student; and also, someinteraction between student and content issignificantly linked to perceived learning.(Aytekin & Fahriye, 2005) suggested thatcommunication barriers are exposed throughthe perspectives of both students and teachersat Eastern Mediterranean University (EMU)online programs and courses, based on thedataobtainedfromqualitativeandquantitative study methods technological,physical, semantic, psychological barriers areconcerned with those barriers.(Kebritchi, Lipschuetz, & Santiague, 2017) intheir research identified three key categories ofoutcomes: problems relating to onlinelearners, teachers, and the creation of content.The challenges faced by learners included n of learners in online courses. Thechallenges of teachers included changingfaculty roles moving from face-to-face toonline, time management, and methods ofteaching. Content concerns included the roleof teachers in the production of content, theincorporation of multimedia into content, therole of instructional strategies in the creationof content, and content developmentCONCEPTUAL FRAMEWORKCovid-19andmodernformsofcommunication have significantly changed theteaching and learning system, n failure has been experiencedby many of us. In many ways online teachinglearning is also covered under this.Expectations and understanding from teachersand students have increased in such pandemicand uncertainty. Threats related to the virusand the impact that the Covid-19 had on thehumanpsychologyincreasedtheinconvenience on student and teacher.Keeping all these parameters, the proposedresearch framework has been conceptualized(figure 1). From the Students' point of view,constructs such as online learning over offlinelearning, barriers of communication andEffective learning outcome were considered.265

techniques of convenient sampling andsnowball technique. The adequacy of thesample size was determined by G Powersoftware G- power softwareestimates the required sample size for thestudy based on the number of predictors andthe desired effect size and probability error.With two predictors the estimated sample sizeby the software was 262, as such sample sizefor the study is considered as adequate basedon which further analysis can be undertaken.The data collected was analysed throughSmart PLS SEM. The latest software is gaininga lot of popularity amongst researchers to theease in analysis and the presentability ofresults.Figure 1: Conceptual FrameworkRESEARCH HYPOTHESESThe following hypotheses were developed forthis research work:H1: There is no significant difference in onlineand offline learning for the students.H2: There are no barriers of communicationfaced by instructors and students.H3: The effective learning outcome is the samein both cases.DISCUSSION AND CONCLUSIONThe demographic profile based on gendershowed that 50.33% were male respondents(228 participants) followed by 49.67% female(225 participants). The demographic profileFigure2: G* Power AnalysisSource: Author’s own calculations.RESEARCH METHODOLOGYThe research study follows an exploratorydescriptive research design. The universe ofthe study is Bhopal, Madhya Pradesh. Thesampling units of the study are the students ofUG and PG in Bhopal, Madhya Pradesh. Fordata collection, structured questionnaire usingestablished scales were used. The data wascollected through non-probability samplingbased on program showed that the highesteducational level of respondents is bachelordegree (UG) with 95.81% (434 participants)followed by master’s degree (PG) with 4.19%(19 participants). Of the 434 UG respondents219 participants were male representing50.46% and 215 respondents were femalerepresenting 49.54% of 434 UG participants. Ofthe 19 PG respondents 9 participants were266

male representing 47.37% and 10 participantswere female representing 52.63% of 19 PGparticipants. Majority of the respondents werefrom UG I Year representing 41.50% (188participants) followed by UG III Year 29.14%(132 participants), UG II Year 25.17% (114participants), PG I semester 2.65% (12participants) and only seven respondents werethere from PG III semester representing 1.54%of the total 453 respondents.Confirmatory Composite AnalysisThe measurement model was analysed for thereliability of the constructs. For the purpose ofthe study Cronbach’s Alpha with a thresholdvalue of 0.7 was analysed. CompositeFigure -3: Measurement ModelTable 1: Summary Analysis of the Demographic Features Using Frequency, Percentage, andCumulative PercentageDemographic FactorsGenderMaleFemaleFrequencyPercentCumulative 19100.0050.4649.54100.0047.3752.63100.0095.81100PG 5025.1729.142.651.54100.00TotalProgramUGPGTotalUG MaleUG FemaleUG TotalPG MalePG FemaleClassUG I YearUG II YearUG III YearPG I SemesterPG III Semesterreliability was also analysed with a thresholdvalue of 0.7. Although a value of 0.5 isconsidered adequate for Average VarianceExtracted (AVE), the value of AVE was morethan 0.7 for all the three constructs (Table 0The table above presents the results of theCronbach Alpha, roh A, Composite Reliabilityand Average Variance extracted. The datashows all the criteria for analysing thereliability of the constructs are met in themodel.Table 2: Results of Confirmatory Composite Analysis, Average Variance Extracted, and ConstructReliabilityCronbach'sComposite Average Variancerho AAlphaReliabilityExtracted (AVE)Barriers of communication0.9560.9570.9620.715Effective Learning Outcome0.9580.9590.9640.772Online Learning over Offline Learning0.8320.8330.9000.749Source: Authors own work.267

DISCRIMINANT VALIDITYTo analyse that the variables under the studyare truly different to each other discriminantvalidity was undertaken. Fornell-LarckerCriterion (1981) and HTMT criteria wasapplied to test discriminant validity. FornellLarcker Criterion is the traditional methodbased on the degree to shared variance that isthere between the variables to evaluate thedegree of shared variance that exists betweenthe latent variables. Table 3 presents FornellLarcker Criterion results which indicate thatthe square root of average variance extractedis higher than crossed correlation constructs,thereby establishing discriminant validity ofthe constructs of the study. HTMT is latestmethod which has gained popularity amongstresearchers to calculate discriminant validityof the constructs. SmartPLS SEM enables toanalyse discriminant validity through HTMT.The threshold value for HTMT is suggested as0.85 (Kline., 2011, Henseler et al., 2015) and0.95 (Teo et al., 2008, Gold et al., 2001). Theresults of the analysis presented in Table 4 areas per the criteria suggested. The results againreaffirm the discriminant validity of theconstructs through HTMT. Thus, resultsestablish discriminant validity of theconstructs and indicates that further analysiscan be undertaken. Table 5 represents Modelfit summary and indicates that the model is fitas SRMR is 0.051 which is less than 0.08 andNFI is 0.871 which is near to 0.90.STRUCTURAL MODEL ASSESSMENTStructural Model assessment for the study wasdone through bootstrapping process in PLSSEM. To analyse the predictive power of themodel and to test the hypothesis 5000bootstraps were employed through thebootstrapping process. The results of theanalysis are presented in figure 4 and tablenumber 6.Figure 4: Structural Equation ModelTable 3: Discriminant ValidityFornell-Larcker CriterionBarriers of communicationEffective Learning OutcomeOnline Learning over Offline LearningBarriers ofcommunicationEffectiveLearning Outcome0.8460.7910.7440.8790.720Online Learningover OfflineLearning0.866Source: Authors own work.Table 4: HETEROTRAIT-MONOTRAIT RATIO (HTMT)Heterotrait-Monotrait Ratio (HTMT)Barriers of communicationEffective Learning OutcomeOnline Learning over Offline LearningBarriers ofcommunicationEffective LearningOutcome0.8220.8300.803Online Learning overOffline LearningSource: Authors own work.Table-5Model Fit SummarySaturated Model0.0510.6060.5031281.1490.870SRMRd ULSd GChi-SquareNFISource: Authors own work.268Estimated Model0.0510.6060.5031281.1490.870

Table 6: Hypotheses Testing Results of the Structural ModelBarriers of communication - Effective Learning OutcomeOnline Learning over Offline Learning - Barriers of communicationOnline Learning over Offline Learning - Effective Learning OutcomeOriginalSample(O)0.5720.7440.294T Statistics( O/STDEV )P Values7.81328.1674.0100.0000.0000.000TABLE 7: STANDARDIZED DIRECT, INDIRECT AND TOTAL EFFECTS OF VARIOUSCONSTRUCTSDependent Variables Barriers of CommunicationEffective Learning OutcomeDEIETEDEIETEIndependent Variables Online Learning overBarriers ofOffline 2Source: Author’s own work.Notes: DE: Direct Effects, IE: Indirect Effects, and TE: Total EffectsCONCLUSIONThe barrier may occur at any stage during thecommunication process (Sending, Encoding,Transmission, Decoding, or Receiving). Sincethis research was undertaken during theCOVID-19 time frame, when students weresupposed to attend online classes, it revealedthe different barriers to communication thatthey experienced. The research uncoveredcommunication barriers among students whoprefer offline classes to online classes.TIMINGS Students have often expressed theopinion that online tutorials do not allowenough time for practical topics, which requirea great deal of personal guidance and dsinanexcellentunderstanding of the topic. Students becomemore alert and active in class with thereflection of the teacher's body language andfacial expressions. The physicality of aninstructor, according to students, is essentialfor a better understanding of the subject. Dueto the distance, students believe thatresponding to teachers through the use of theinternet is not as quick as it is in person.FAULTY PLANNING Since each subjectnecessitates a different set of materials andteaching styles, some topics include handoutsor worksheets, and others necessitate audio,video, or other activities, online classes fallshort of meeting these requirements.INFORMATION OVERLOAD Many of therespondents have seen this barrier becausethey have to attend lectures on differentsubjects three to four times a day for 45-55minutes with a short break, which leaves themparalyzed due to the overload of learning.ENVIRONMENTAL SETTINGSSurroundings are crucial because, in an onlinesetting, each student is seated in a differentphysical environment, which can be peacefulor distracting. The traditional classroomsetting provides all the students with acommon physical environment, which notonly helps them to concentrate on their studiesbut also motivates them to work together.TECHNICAL BARRIER (NOISE) Technicalbarriers are generated by digital disruptions toInternet access, such as glitches or screen lag,visibility and audibility problems, a lack oftechnical expertise, inadequate preparation,and unfamiliarity with learning software’screates technical barriers.PERSONAL BARRIERS Students haveclaimed that taking online classes has raisedtheir costs (internet data, smartphone, etc).269

The use of a computer has weakened theireyesight, and the repetition of the same bodypostures for extended periods has resulted inmental health problems, sadness, and anindiscipline routine. Students complainedabout interruptions while studying at homeand expressed dissatisfaction with the classsize. Students believed that teachers lackedexpertise in online learning tools for deliveringclasses, as well as class participation skills.Online learning is not tailored to the needs ofstudents, there is a shortage of academicadvisors due to the online system, and onlinecourse materials are not delivered on time.They also reported difficulty in contactingacademic or administrative staff and onlineactivities are difficult than offline activitiesa way that motivates responses and tries to getimmediate feedback from students, and bydeveloping the class in a more interactive wayso that students can learn more effectively.Off-screen time should be provided, and someonline physical activities or ice-breakingsessions should be added.The class size should be structured in such away that specific groups can be handledindividually. For the timely availability ofclass counseling services and study nces, virtual webinars, chat-basedonline discussions) and synchronous (phonecalls or video meetings) approaches should beused. To make the learning process easier forstudents and prevent misunderstanding, aunified LMS should be developed, and acommon forum should be used by all facultymembers. Students should be given the sameamount of time to express themselves. Classschedules should not be irregular orinconvenient for students.PSYCHOLOGICAL BARRIERS Studentshave shared feelings of unfairness, unbelongingness, and a lack of motivation, aswell as the fact that classes are more difficultand less pleasant, and that it is better suitedfor active students rather than introverts. Theyalso claimed that online classes necessitatedthe help of family and friends.Students' presentations and class engagementactivities should be made a prerequisite in allcolleges. To avoid the issue of informationoverload and to facilitate effective listening, anonline class should be a combination of bothformal and informal interactions.PERCEPTIONAL BARRIERS In onlinecourses, the learning environment isdemotivating, and personal analytical abilities,speaking skills, expression of thoughts, andconfidence have all deteriorated. Onlinecourses lack the opportunity to link academiaand business, and practical principles are lessclear. Online classes do not have much in theway of skills enhancement because they aredull. Overall, online classes do not have anappropriate learning environment.LIMITATIONS AND FURTHER STUDYSince this research is limited to student’sexperiences, data from educators should becollected as well to learn about the challengesthey face. Data from primary and secondaryschools are not collected, limiting the scope ofthis report. The information for this study wasgathered primarily from residents of Bhopaland the surrounding area, and it was limitedto Madhya Pradesh. Furthermore, data wasgathered using a Google Form and distributedto people who were either directly orindirectly acquainted with the researcher.RECOMMENDATIONSTo eliminate the problem of long physicaldistance, a personal touch should be present;for technological errors, good internetconnectivity and equipment should beensured to avoid lags and glitches. Institutesshould provide instructors with facultydevelopment programs and ready reckonersto ensure that classes run smoothly. Timemanagement and scheduling can beconducted in such a way that practical ordifficult subjects can be accommodated, andstudents can stay focused in class.These barriers can be overcome by systematicplanning for lectures, by preparing the studymaterial that is rich in content, imaginative,and easy to understand, by communicating inThe study overlooked a broader segment ofsociety, such as people from remote regions,people from other states in the country, andpeople from all over the world. Their onlinelearning experiences would almost certainlyhave affected the findings of this report.Furthermore, the analysis avoids constructsthat may have explained the relevance of thecurrent study, suggesting the likelihood ofconducting rigorous research on those270

constructs in the future using cross-countrylongitudinal data.Program and Courses. Turkish OnlineJournal of Distance Education, 6, 1111.Kebritchi, M., Lipschuetz, A., & Santiague, L.(2017, 09 01). Issues and Challenges forTeaching Successful Online Courses inHigher Education: A Literature Review.Journal of Educational Technology 9516661713ReferencesMonkhouse, W. S. (1992). M.J.T. FitzGerald:UndergraduateMedicalAnatomyTeaching: Journal of Anatomy (1992) 180,203-209 [1]. Journal of Anatomy, 181, 177–177.Abu , B., Kiramat , S., & Xu , Q. (2020). TheEffect Of Communication Barriers OnDistance Learners Achievements. RevistaArgentina de Clínica Psicológica, 248-264.doi: 10.24205/03276716.2020.1027Khanna, D., & Prasad, A. (2020). ProblemsFaced by Students and Teachers DuringOnline Education Due to COVID-19 andHow to Resolve Them. 2020 6thInternational Conference on Educationand Technology (ICET) (pp. 0.1109/ICET51153.2020.9276625Aynur , S., Tülay , A., & Zülfiye , A. (2015).Communication Barriers in OnlineTeaching and Online Learning withdigital media, in the Framework lConference on Communication, Media,Technology and Design (pp. 57-68).Dubai: XYZ.Shiva, Narula, & Shahi, (2020). What drivesretail investors’ investment decisions?Evidence from no mobile phone phobia(nomophobia) and investor fear ofmissing out (I – FOMO). Journal ofContent, Community & Communication, 11,pp.2-20.Muilenburg, L., & Berge, Z. (2005, 05 01).Student Barriers to Online Learning: AFactorAnalyticStudy.DistanceEducation-DISTANCE EDUC, 26(1), Gilitwala, B., & Nag, A. K. (2020). ImpactAssessment of Factors Influencing User’SContinuance Intention To Use Near FieldCommunication (Nfc). Journal of Content,Community and Communication, 12, bramenka, V. (2015). Students’ Motivationsand Barriers to Online Education. 7, 1–72. Kumar Bhagat, Leon Yufeng Wu, &Chun-Yen Chang. (2016). Development andValidation of the Perception of StudentsTowardsOnlineLearning(POSTOL). JournalofEducationalTechnology & Society, 19(1), 350-359.Retrieved February 10, 2021, .350Marks, R., Sibley, S., & Arbaugh, J. (2005, 0801). A Structural Equation Model ofPredictors for Effective Online Learning.Journal of Management Education, 2904271199Dabaj, F., & Yetkin, A. (2020). Analysis ofCommunication Barriers to DistanceEducation: A Review Study. OnlineJournal of Communication and 9333/ojcmt/2328Fornell , C. G., & Larcker, D. F. (1981).Evaluating Structural Equation ModelswithUnobervableVariablesandMeasurement Errors. Journal of MarketingResearch , 18 (1), 39-50.Aytekin, I., & Fahriye, A. (2005, 10 1).Communication Barriers: A Study ofEasternMediterraneanUniversityStudents' and Teachers' of OnlineKline, R. B. (2011). Methodology in the SocialSciences: Principles and Practice ofStructural Equation Modeling (3rd ed.).Guilford Press.271

Henseler , J., Ringle , C. M., & Sarstedt, M.(2015). A New Criterion for AssesingDiscriminant Validity in Variance-BasedStructural Equation Modeling. Journal ofAcademy of Markeing Science , 43 (1), 115135.Model (TAM). Journal of ComputerAssisted Learning , 24 (2), 128-143.Gold, A. H., Malhotra, A., & Segars, A. H.(2001). Knowledge Management: AnOrganizational Capabilities Perspective.Journal of Management Information Systems, 18 (1), 185-214.Teo, T., Lee, C. B., & Chai, C. S. (2008).Understanding Pre-Service Teacher'sComputer Attitudes: Applying andExtending the Technology Acceptance***272

students' achievement and the communication barriers they encountered while attending the classes. The study's constructs were online learning vs. offline learning, communication barriers, and effective learning outcomes. Design

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