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Technology Acceptance for Online Teaching-Learning: Perspectives of Teachers from Higher Education in India

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Title: Technology Acceptance for Online Teaching-Learning: Perspectives of Teachers from Higher Education in India
Language: English
Authors: Kamble, Aakash (ORCID 0000-0002-6152-302X), Golhar, Devidas (ORCID 0000-0001-5131-8092), Kalkar, Parag (ORCID 0000-0002-3768-3621)
Source: Educational Media International. 2022 59(4):324-340.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 17
Publication Date: 2022
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Foreign Countries, COVID-19, Pandemics, Educational Technology, Electronic Learning, Teacher Attitudes, College Faculty, Value Judgment, Usability, Affordances, Intention
Geographic Terms: India
DOI: 10.1080/09523987.2022.2153989
ISSN: 0952-3987
1469-5790
Abstract: The sudden outbreak of the COVID-19 pandemic resulted in a transition to an online teaching-learning (OTL) methodology, forcing India's institutions to adopt it. The present study investigates OTL's acceptance by faculty instructors/teachers employed in India's higher educational institutions using the technology acceptance model (TAM). A survey of 433 respondents studied the intention to use OTL by teachers. The study considered India's higher educational institutions and utilized web-based questionnaire survey methods for collecting the responses. The study found support for OTL's perceived usefulness and the perceived ease of use, facilitating conditions to be significant determinants for attitude towards the use of technology by users. The study introduced service conditions related to the faculty instructor/teacher's employment in the higher educational institutions and its bearing on their work routine. The study did not find service conditions as a significant determinant of attitude towards using OTL technology. The results present evidence of a valid model to predict technology acceptance among India's teachers.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1377034
Database: ERIC
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  Value: <anid>AN0161687280;5b101dec.22;2023Feb07.03:50;v2.2.500</anid> <title id="AN0161687280-1">Technology acceptance for online teaching-learning: perspectives of teachers from higher education in India </title> <p>The sudden outbreak of the Covid-19 pandemic resulted in a transition to an online teaching-learning (OTL) methodology, forcing India's institutions to adopt it. The present study investigates OTL's acceptance by faculty instructors/teachers employed in India's higher educational institutions using the technology acceptance model (TAM). A survey of 433 respondents studied the intention to use OTL by teachers. The study considered India's higher educational institutions and utilized web-based questionnaire survey methods for collecting the responses. The study found support for OTL's perceived usefulness and the perceived ease of use, facilitating conditions to be significant determinants for attitude towards the use of technology by users. The study introduced service conditions related to the faculty instructor/teacher's employment in the higher educational institutions and its bearing on their work routine. The study did not find service conditions as a significant determinant of attitude towards using OTL technology. The results present evidence of a valid model to predict technology acceptance among India's teachers.</p> <p>Keywords: Technology acceptance; online teaching-learning; online learning environments; higher education; India</p> <hd id="AN0161687280-2">Introduction</hd> <p>In the face of external challenges, higher education institutions had to implement learning technologies to disseminate knowledge among the learners and enhance teaching. In the wake of the SARS-CoV-2 pandemic, higher education institutions switched over to online teaching-learning methodology. In the present study, online teaching-learning (OTL) refers to higher education institutions conducting programs and courses using digital technology due to the teacher and the learner's physical distance. Indian institutions are of three major types based on their adoption of the online education model. The ones who already had the digital infrastructure, those with digital infrastructure but with optimal utilization capabilities, and those without any online infrastructure (Majumdar & Pathak, [<reflink idref="bib25" id="ref1">25</reflink>]). The latter two aspects are particularly evident in affiliated institutions that lack the technological infrastructure to transition to online teaching-learning or lack optimizing and utilizing it.</p> <p>According to Warsi ([<reflink idref="bib48" id="ref2">48</reflink>]), the transition towards online teaching-learning has been smooth for private universities compared to public institutions adapting to these changes. The article further highlights the concerns related to internet connectivity and lack of infrastructure in rural areas worldwide, with frequent power cuts being the norm in such areas. The transition towards OTL and the adoption of this technology mainly depends on the challenging aspects related to the internet and power infrastructure, accessibility to the online medium, and the soft aspects of the acceptance and usage of OTL by the faculty. Additionally, some enterprises have successfully introduced web-based e-learning as a platform for employees' education and training, thus creating a shared learning environment and strengthening employees' professionalism and information-related competencies (Warsi, [<reflink idref="bib48" id="ref3">48</reflink>]).</p> <p>From the viewpoint of the faculty's initiative to embrace online teaching, earlier studies have suggested a reluctance towards such technologies owing to fear of change, reliability, and usability of the technology, proficiency in the use of technology, increased workload, and skepticism over student outcomes (Bolliger & Wasilik, [<reflink idref="bib11" id="ref4">11</reflink>]; McQuiggan, [<reflink idref="bib29" id="ref5">29</reflink>]). Also, the mere availability of technological infrastructure does not determine the acceptance and adoption of new methodologies from the faculty and the learners (Persico et al., [<reflink idref="bib32" id="ref6">32</reflink>]). Earlier studies have also highlighted the notion of universities and institutions being willing to use the technology and the innovative, collaborative online methods and the overall fit of OTL's in the institutional structure. Further, the teacher's beliefs that they were skilled in using technology were significantly correlated with their intention to participate in online education (Tabata & Johnsrud, [<reflink idref="bib39" id="ref7">39</reflink>]). Hence, a teacher's previous success with other technologies and their confidence in their computer skills play a critical role in their willingness to teach online (Osika et al., [<reflink idref="bib31" id="ref8">31</reflink>]). Studies in the past have revealed concerns among faculty regarding their perceived barriers to student success in online classes, uncertainty about their image as online instructors, technical support needs, and their desire for reasonable workload and manageable class enrolments in online courses (Wingo et al., [<reflink idref="bib49" id="ref9">49</reflink>]).</p> <p>In the COVID-19 pandemic context, higher educational institutions were affected, disrupting their teaching-learning and assessment systems. The higher educational institutions adopted OTL systems to circumvent the stoppage due to force majeure. The study aims to investigate the acceptance of online teaching-learning by the teaching faculty in India. The study uses an extended technology acceptance model developed by Davis ([<reflink idref="bib13" id="ref10">13</reflink>]) with extensions to the theoretical framework incorporating facilitating conditions (Thompson et al., [<reflink idref="bib44" id="ref11">44</reflink>]) and introduces service conditions variables influencing teachers' attitude towards online teaching-learning. Service conditions refer to teachers' employment status in higher education institutions with significant variances in their roles and responsibilities. The study's outcome intends to provide possible insights to all the higher education stakeholders (particularly the affiliated undergraduate and postgraduate institutions) in planning, operationalizing, and disseminating their online education.</p> <hd id="AN0161687280-3">Literature review</hd> <p></p> <hd id="AN0161687280-4">Technology acceptance model</hd> <p>TAM derived from the theory of reasoned action (TRA), which was developed by Ajzen and Fishbein ([<reflink idref="bib1" id="ref12">1</reflink>]) and further developed to examine the adoption of computer information systems in the workplace by users (Davis, [<reflink idref="bib13" id="ref13">13</reflink>]). Acceptance of new technology by the users and its perceived usability is essential for developing such innovative technologies (Holden & Rada, [<reflink idref="bib18" id="ref14">18</reflink>]). The technology acceptance model predicts the acceptance of the user and the use of any given information technology. Constructs in TAM are based on the "causal relationships among the external variables, beliefs, and attitudinal constructs and the actual usage" (Hubona & Kennick, [<reflink idref="bib21" id="ref15">21</reflink>], p. 166). When offered with innovative or new technology, the perceived usefulness, and ease of use influence the user's decision about how and when to use it. The perceived usefulness and ease of use represent the users' cognitive responses towards technology use. The cognitive responses further influence the users' affective (attitude) responses to technology use, ultimately driving the behavioral response of technology use (Turner et al., [<reflink idref="bib45" id="ref16">45</reflink>]).</p> <hd id="AN0161687280-5">Antecedents of technology acceptance</hd> <p>The three antecedents are considered essential in the present study on teachers' acceptance of online teaching-learning. The first is the teachers' behavioral beliefs towards probable outcomes arising from the behavior and the judgments about these outcomes. For a teacher/instructor, their attitude towards using any technology takes a central position to successfully accept and adopt such technology (Huang & Liaw, [<reflink idref="bib20" id="ref17">20</reflink>]). Second, normative beliefs deal with other people's expectations and the motivations to adhere to those expectations. Like the subjective norm, the normative belief evolves from the perceived pressures on an individual to perform in a given situation and the individual's motivation to act under such pressure. For a teacher/instructor, the subjective norm refers to the degree to which they perceive the use of technology at times due to the pressure from the institute's management, parents, and teachers (Sugar et al., [<reflink idref="bib37" id="ref18">37</reflink>]). Thirdly the control beliefs are all about the external (infrastructure and computer access) and internal (skills and abilities) beliefs of a teacher/instructor. The conducive conditions depend on the teacher's belief in the organizational and technological infrastructure for using technology. These conditions significantly predict intention (Teo, [<reflink idref="bib41" id="ref19">41</reflink>]; Venkatesh et al., [<reflink idref="bib47" id="ref20">47</reflink>]). Based on these three beliefs, the authors consider service conditions that deal with the fears arising from their beliefs towards accepting an OTL and conducting online teaching.</p> <hd id="AN0161687280-6">Existing studies on teacher's acceptance of technology</hd> <p>"Acceptance, in general, refers to the consenting action of an individual to receive the offered" (Taherdoost, [<reflink idref="bib40" id="ref21">40</reflink>], p. 31). Various researchers have different aspects and have observed diffusion of e-learning in an organization, acceptance of new information systems, communications between humans and computers, psychological aspects of e-learning, and pedagogical issues (Babić, [<reflink idref="bib4" id="ref22">4</reflink>]). Earlier research has focused on the use of e-learning in instruction by the teacher, investigation in the characteristics of faculty and the behaviors in an online MBA program (Arbaugh, [<reflink idref="bib3" id="ref23">3</reflink>]), and factors affecting the acceptance of e-learning courses by teachers (Hrtoňová et al., [<reflink idref="bib19" id="ref24">19</reflink>]). The most important predictor of teachers' start and continuance of technology in teaching is their acceptance of technology (Šumak et al., [<reflink idref="bib38" id="ref25">38</reflink>]). TAM is the most widely used and helpful in explaining teachers' educational technology (Šumak et al., [<reflink idref="bib38" id="ref26">38</reflink>]). Though numerous studies are available on the technology acceptance of teachers/instructors for various learning methodologies, no previous study has investigated the sudden transition of teachers to OTL due to force majeure caused by the pandemic in universities, affiliated institutions, and autonomous institutions engaged in higher education.</p> <hd id="AN0161687280-7">Hypothesis development</hd> <p>This section presents the research hypotheses based on the technology acceptance model (TAM) by Davis ([<reflink idref="bib13" id="ref27">13</reflink>]). The model is an adaptation of the TAM and modified to suit the purpose of the study. The technology used is the users' behavioral intentions towards the technology, determined by the attitude towards the use and perceived usefulness. Perceived usefulness of the technology and the perceived ease of use of the technology jointly determine its attitude. It is important to note that the hypotheses in this study are to be considered for technology acceptance of online teaching by teachers/facilitators/instructors.</p> <hd id="AN0161687280-8">Perceived usefulness</hd> <p>The definition of perceived usefulness (PU) is adapted from the original definition proposed by Davis et al. ([<reflink idref="bib14" id="ref28">14</reflink>]). In this research, perceived usefulness is how a teacher believes that using an OTL will enhance their performance at the institute and employability. Earlier studies have shown evidence about teachers' beliefs and job performance (Luan & Teo, [<reflink idref="bib24" id="ref29">24</reflink>]). We propose the following hypothesis based on the earlier studies (Davis et al., [<reflink idref="bib14" id="ref30">14</reflink>]).</p> <p> <bold>H1</bold>: Perceived usefulness will have a significant influence on attitude toward usage.</p> <hd id="AN0161687280-9">Perceived ease of use</hd> <p>Perceived ease of use (PEOU) is how the teacher believes transitioning to an online teaching modality will be free from effort. Though the users accept the technology as being useful, the technology's learning process, if steep, may outweigh the usefulness and benefits of adopting the technology (Davis, [<reflink idref="bib13" id="ref31">13</reflink>]). Perceived ease of use indirectly influences attitudes through perceived usefulness apart from directly influencing attitude. We propose the following hypothesis.</p> <p> <bold>H2</bold>: Perceived ease of use will significantly influence attitude toward usage.</p> <p> <bold>H3</bold>: Perceived ease of use will significantly influence perceived usefulness.</p> <hd id="AN0161687280-10">Facilitating conditions</hd> <p>Facilitating conditions (FC) is the "degree to which an individual believes an organizational and technical infrastructure exists to support the use of the system" (Venkatesh et al., [<reflink idref="bib47" id="ref32">47</reflink>], p. 453). For the study, facilitating conditions are the degree to which the teacher believes information and communication technology infrastructure and technical support for online teaching while conducting courses. Facilitating conditions towards using technology is significant (Venkatesh et al., [<reflink idref="bib47" id="ref33">47</reflink>]). Availability of resources for assistance and support required by the teacher creates a positive attitude towards online learning platforms, thus ensuring facilitating conditions. The presence of resources and assistance provides an impetus for using new technologies (Bervell & Arkorful, [<reflink idref="bib9" id="ref34">9</reflink>]; Bervell & Umar, [<reflink idref="bib10" id="ref35">10</reflink>]). Earlier studies by Bervell and Arkorful ([<reflink idref="bib9" id="ref36">9</reflink>]) established a positive and significant relationship between the organization's conducive environment for technology adoption and users' behavior toward the technology. The study thus proposes:</p> <p> <bold>H4</bold>: Facilitating conditions have a significant influence on attitude toward usage.</p> <p> <bold>H5</bold>: Facilitating conditions have a significant influence on perceived ease of use.</p> <hd id="AN0161687280-11">Service conditions</hd> <p>Teachers employed in elementary schools to universities are ubiquitous and can differ considerably depending on the institutions. Aspects that affect a teacher's job satisfaction can be "teachers' feelings of competence, administrative control, and organizational culture" (Ma & MacMillan, [<reflink idref="bib26" id="ref37">26</reflink>]). The service conditions in Indian institutions and universities depend on the management's administrative control and the organizational culture, with importance to other tasks and roles apart from teaching. Evidence has suggested that excessive paperwork and administrative tasks lead to teachers' withdrawal from participation (Albert & Levine, [<reflink idref="bib2" id="ref38">2</reflink>]). While focusing on the employment and service conditions of contractual teachers in India, they are underpaid, with little or no training, depleted motivation levels due to fear of job loss, and at times demanding work environment (Kumari, [<reflink idref="bib22" id="ref39">22</reflink>]). For teachers to remain in academics and also achieve job satisfaction, the intrinsic factors (satisfaction and motivation arising from teaching) and extrinsic factors (remuneration, availability of resources, and support) play a vital role (Sharma & Jyoti, [<reflink idref="bib36" id="ref40">36</reflink>]).</p> <p>Online teaching-learning methods have been predominantly present globally for the past two decades. Despite this, there have been apprehensions by faculty members/teachers/instructors over the years to embrace online teaching methodologies (Wright, [<reflink idref="bib50" id="ref41">50</reflink>]). Mitchell and Geva-May conclude that "one key variable leading to implementation problems that are acknowledged in the literature is the resistance of actors in organizational systems to take up new initiatives and change the status quo" (Mitchell & Geva-May, [<reflink idref="bib30" id="ref42">30</reflink>], p. 72). Online teaching was less rigorous than face-to-face classroom teaching, yet a significant amount of time is required to prepare for the session, thus obstructing the adoption of online learning (Wright, [<reflink idref="bib50" id="ref43">50</reflink>]). The increased focus on fiscal accountability by universities and institutions streamlining expenses and onboarding of adjunct or part-time visiting teachers to meet the teaching requirements (Mandernach et al., [<reflink idref="bib27" id="ref44">27</reflink>]). The incongruity between organizational objectives related to online learning environments and the teachers' interests, values, and beliefs create resistance to implementing online teaching (Matland, [<reflink idref="bib28" id="ref45">28</reflink>]). Based on it, we propose new variable service conditions and the hypotheses as follows:</p> <p> <bold>H6</bold>: Service conditions significantly influence attitude towards usage of online teaching-learning.</p> <hd id="AN0161687280-12">Attitude towards use</hd> <p>The users of technology weigh in the attitude towards the use of technology based on the user's perceived usefulness and ease of use. Over the years, the technology acceptance model (TAM) has been used to study teachers' acceptance of technology in the teaching-learning process and is being found to possess predictive validity in several studies (Scherer et al., [<reflink idref="bib35" id="ref46">35</reflink>]; Šumak et al., [<reflink idref="bib38" id="ref47">38</reflink>]; Teo, [<reflink idref="bib41" id="ref48">41</reflink>]). Teachers' negative attitudes towards computer use in the teaching process can impact the learning process for students as well (Yildirim, [<reflink idref="bib51" id="ref49">51</reflink>]). The authors propose that teachers accept online learning systems and possess an a' positive attitude towards them.</p> <p> <bold>H7</bold>: Attitude toward use will significantly influence behavioral intention to use.</p> <p>The hypothesized model is depicted in Figure 1.</p> <p>Graph: Hypothesized model.</p> <hd id="AN0161687280-13">Materials and methods</hd> <p>An online web-based survey was conducted using a structured questionnaire to assess the online teaching-learning environment's acceptance. The study adopted the questionnaire items measuring perceived usefulness (PU), perceived ease of use (PEOU), attitude (AT), and intention to use (IT) from earlier studied and validated technology acceptance model studies (Davis, [<reflink idref="bib13" id="ref50">13</reflink>]; Davis et al., [<reflink idref="bib14" id="ref51">14</reflink>]; Fishbein & Ajzen, [<reflink idref="bib16" id="ref52">16</reflink>]; Venkatesh & Davis, [<reflink idref="bib46" id="ref53">46</reflink>]; Venkatesh et al., [<reflink idref="bib47" id="ref54">47</reflink>]). Further, the study considered facilitating conditions (FC) adopted from Thompson et al. ([<reflink idref="bib44" id="ref55">44</reflink>]) and service conditions (SC) adopted from Mandernach et al. ([<reflink idref="bib27" id="ref56">27</reflink>]) and Wright ([<reflink idref="bib50" id="ref57">50</reflink>]). Researchers slightly modified the questionnaire items in the online learning context considered for the study. The reliability test results portrayed a strong internal consistency with Cronbach's α values greater than 0.7.</p> <p>The questionnaire used web-based survey methods in India from June to July 2020. Each statement had a five-point Likert scale anchored by 1 ("strongly disagree") and 5 ("strongly agree"). A total of 433 teachers/ faculty members/ instructors participated in the survey, who were users of online/ virtual learning environments and had conducted sessions over technology platforms (Zoom, Microsoft Teams, Google Meet) for at least a month. The respondents consisted of 207 (47.8) females and 224 (51.7%) males. Table 1 reports the demographic profile of the respondents. The study employed the maximum likelihood estimation method to perform a confirmatory factor analysis (CFA) and structural equation modeling (SEM) in AMOS 22. The reliability and validity of the measurements used for the proposed factor structure were examined via CFA. Simultaneously, the strength and direction of the hypothesized causal paths among the constructs were analyzed via SEM.</p> <p>Table 1. Details of demographic characteristics.</p> <p> <ephtml> <table><thead><tr><td /><td>Frequency</td><td>Percentage</td></tr></thead><tbody><tr><td>Age Group (in years)</td></tr><tr><td>21 to 30</td><td>39</td><td>9.0</td></tr><tr><td>31 to 40</td><td>191</td><td>44.1</td></tr><tr><td>41 to 50</td><td>138</td><td>31.9</td></tr><tr><td>51 to 60</td><td>60</td><td>13.9</td></tr><tr><td>61 and above</td><td>5</td><td>1.2</td></tr><tr><td>Gender</td></tr><tr><td>Female</td><td>207</td><td>47.8</td></tr><tr><td>Male</td><td>224</td><td>51.7</td></tr><tr><td>Prefer not to say</td><td>1</td><td>.2</td></tr><tr><td>Academic Qualification</td></tr><tr><td>Graduate degree</td><td>3</td><td>.7</td></tr><tr><td>Postgraduate degree</td><td>181</td><td>41.8</td></tr><tr><td>Postgraduate with M. Phil</td><td>32</td><td>7.4</td></tr><tr><td>Doctorate</td><td>217</td><td>50.1</td></tr><tr><td>Academic Experience (in years)</td></tr><tr><td>0 to 2</td><td>16</td><td>3.7</td></tr><tr><td>3 to 5</td><td>37</td><td>8.5</td></tr><tr><td>6 to 10</td><td>122</td><td>28.2</td></tr><tr><td>11 to 20</td><td>189</td><td>43.6</td></tr><tr><td>21 years and above</td><td>69</td><td>15.9</td></tr><tr><td>Employed with</td></tr><tr><td>Undergraduate college/institute</td><td>122</td><td>28.2</td></tr><tr><td>Postgraduate college/institute</td><td>288</td><td>66.5</td></tr><tr><td>University Department</td><td>14</td><td>3.2</td></tr><tr><td>Other</td><td>9</td><td>2.1</td></tr><tr><td>Status of the workstation at the workplace</td></tr><tr><td>have a dedicated/allotted computer</td><td>311</td><td>71.8</td></tr><tr><td>shared computer</td><td>88</td><td>20.3</td></tr><tr><td>no computer</td><td>26</td><td>6.0</td></tr><tr><td>Other</td><td>8</td><td>1.8</td></tr><tr><td>Total</td><td>433</td><td>100.0</td></tr><tr><td>Familiarity with online/virtual learning environments</td></tr><tr><td>Very familiar</td><td>141</td><td>32.6</td></tr><tr><td>Moderately Familiar</td><td>246</td><td>56.8</td></tr><tr><td>Neutral</td><td>36</td><td>8.3</td></tr><tr><td>Unfamiliar</td><td>6</td><td>1.4</td></tr><tr><td>Completely unfamiliar</td><td>4</td><td>.9</td></tr><tr><td>Note: n = 433</td><td /><td /></tr></tbody></table> </ephtml> </p> <hd id="AN0161687280-14">Results</hd> <p></p> <hd id="AN0161687280-15">Measurement model</hd> <p>As seen in Table 2, the confirmatory factor analysis results of the measurement model's fit indices were above the minimum recommended values in earlier studies (P M Bentler & Bonett, [<reflink idref="bib7" id="ref58">7</reflink>]; Bentler, Peter, [<reflink idref="bib8" id="ref59">8</reflink>]; Hair et al., [<reflink idref="bib17" id="ref60">17</reflink>]). The ratio of χ2 to the degrees of freedom (χ2/df) = 2.144, goodness-of-fit index (GFI) = 0.926, comparative fit index (CFI) = 0.966, Tucker-Lewis index (TLI) = 0.960, normed fit index (NFI) = 0.939, and root mean square error of approximation (RMSEA) = 0.051.</p> <p>Table 2. Measurement model fit indices.</p> <p> <ephtml> <table><thead><tr><td>Fit index</td><td>Measurement model</td><td>Recommended Model</td></tr></thead><tbody><tr><td>χ2/df</td><td>2.144</td><td>⩽3.00</td></tr><tr><td>GFI</td><td>0.926</td><td>⩾0.80</td></tr><tr><td>CFI</td><td>0.966</td><td>⩾0.92</td></tr><tr><td>TLI</td><td>0.960</td><td>⩾0.90</td></tr><tr><td>NFI</td><td>0.939</td><td>⩾0.90</td></tr><tr><td>RMSEA</td><td>0.051</td><td>⩽0.08</td></tr></tbody></table> </ephtml> </p> <p>Analysis saw robust internal reliability for the measurement model and convergent and discriminant validity. The values of Cronbach's α were above 0.70, with the questionnaire items having factor loadings of over 0.70 and average variance extracted (AVE) 0.50. Ferketich ([<reflink idref="bib15" id="ref61">15</reflink>]) recommended that corrected item-total correlations range between.30 and.70 for a good scale. The values for item-total correlation were well within the recommendations from earlier studies. The details are mentioned below in Table 3. The square roots of the AVEs of all observed variables were more prominent than the inter-correlations between the variables (see, Table 4).</p> <p>Table 3. Internal reliability and convergent validity of the measurements.</p> <p> <ephtml> <table><thead><tr><td>Construct</td><td>Internal reliability</td><td>Convergent and discriminant validity</td></tr><tr><td>Item</td><td>Cronbach's α</td><td>Item-total correlation</td><td>Factor loading</td><td>Composite reliability</td><td>Average variance extracted</td></tr></thead><tbody><tr><td>Perceived usefulness</td><td>PU1</td><td>0.906</td><td>0.654</td><td>0.843</td><td>0.892</td><td>0.626</td></tr><tr><td>PU2</td><td /><td>0.644</td><td>0.842</td><td /><td /></tr><tr><td>PU3</td><td /><td>0.655</td><td>0.809</td><td /><td /></tr><tr><td>PU4</td><td /><td>0.603</td><td>0.795</td><td /><td /></tr><tr><td>PU5</td><td /><td>0.656</td><td>0.651</td><td /><td /></tr><tr><td>Perceived ease of use</td><td>PEOU1</td><td>0.876</td><td>0.675</td><td>0.816</td><td>0.844</td><td>0.577</td></tr><tr><td>PEOU2</td><td /><td>0.790</td><td>0.801</td><td /><td /></tr><tr><td>PEOU3</td><td /><td>0.636</td><td>0.716</td><td /><td /></tr><tr><td>PEOU4</td><td /><td>0.636</td><td>0.700</td><td /><td /></tr><tr><td>Intention to use</td><td>IT1</td><td>0.900</td><td>0.685</td><td>0.826</td><td>0.780</td><td>0.570</td></tr><tr><td>IT2</td><td /><td>0.678</td><td>0.768</td><td /><td /></tr><tr><td>IT3</td><td /><td>0.683</td><td>0.737</td><td /><td /></tr><tr><td>IT4</td><td /><td>0.698</td><td>0.702</td><td /><td /></tr><tr><td>Attitude</td><td>AT1</td><td>0.886</td><td>0.667</td><td>0.859</td><td>0.693</td><td>0.629</td></tr><tr><td>AT2</td><td /><td>0.673</td><td>0.806</td><td /><td /></tr><tr><td>AT3</td><td /><td>0.626</td><td>0.775</td><td /><td /></tr><tr><td>Facilitating Conditions</td><td>FC1</td><td>0.912</td><td>0.719</td><td>0.909</td><td>0.694</td><td>0.631</td></tr><tr><td>FC2</td><td /><td>0.620</td><td>0.882</td><td /><td /></tr><tr><td>FC3</td><td /><td>0.628</td><td>0.855</td><td /><td /></tr><tr><td>Service conditions</td><td>SC1</td><td>0.727</td><td>0.714</td><td>0.883</td><td>0.761</td><td>0.545</td></tr><tr><td>SC2</td><td /><td>0.680</td><td>0.809</td><td /><td /></tr><tr><td>SC3</td><td /><td>0.661</td><td>0.744</td><td /><td /></tr><tr><td>SC4</td><td /><td>0.609</td><td>0.486</td><td /><td /></tr></tbody></table> </ephtml> </p> <p>Table 4. Discriminant validity of the measurements.</p> <p> <ephtml> <table><thead><tr><td /><td>PEOU</td><td>PU</td><td>AT</td><td>IT</td><td>FC</td><td>SC</td></tr></thead><tbody><tr><td>PEOU</td><td>0.791</td><td /><td /><td /><td /><td /></tr><tr><td>PU</td><td>0.575</td><td>0.759</td><td /><td /><td /><td /></tr><tr><td>AT</td><td>0.633</td><td>0.619</td><td>0.754</td><td /><td /><td /></tr><tr><td>IT</td><td>0.674</td><td>0.609</td><td>0.750</td><td>0.793</td><td /><td /></tr><tr><td>FC</td><td>0.396</td><td>0.383</td><td>0.400</td><td>0.396</td><td>0.794</td><td /></tr><tr><td>SC</td><td>0.368</td><td>0.343</td><td>0.428</td><td>0.419</td><td>0.414</td><td>0.738</td></tr></tbody></table> </ephtml> </p> <p>1 Notes: PEOU- perceived ease of use; PU- perceived usefulness AT- attitude; IT- intention to use; FC- facilitating conditions; SC- service conditions. Diagonal elements in italics represent the square roots of the average variance extracted.</p> <hd id="AN0161687280-16">Structural model and hypothesis test</hd> <p>The structural model showed satisfactory levels of fit indices as per the results indicated in SEM (see, Table 2): χ2/df = 2.144, GFI = 0.926, CFI = 0.966, TLI = 0.960, NFI = 0.939, and RMSEA = 0.051. As seen in Figure 2 and Table 5, the respondents' perceived usefulness of online teaching positively correlated with their attitude towards its use (β = 0.43, p < 0.001). It provided support for H1. The teachers' perceived ease of use of online teaching bore a positive significant relationship and influence over their attitude toward using it (β = 0.381, p < 0.001), and thus H2 was supported. The perceived ease of use positively correlated with the respondents' perceived usefulness of online teaching (β = 0.349, p < 0.001), thus supporting H3. Facilitating conditions for adopting online teaching methods positively influenced the teacher's attitude towards using it (β = 0.305, p < 0.001), hence supporting H4. As hypothesized, facilitating conditions positively affected perceived usefulness (β = 0.311, p < 0.001), supporting hypothesis H5. The service conditions to attitude (SC→AT) path (H6, β = 0.02, p = 0.071), all proposed paths were significant for the structural model's standardized coefficients. Consistent with earlier studies, attitude towards online teaching had a significant positive influence over behavioral intention (β = 0.266, p < 0.001), supporting H7.</p> <p>Graph: Figure 2. Model results.</p> <p>Table 5. Summary of hypothesis tests.</p> <p> <ephtml> <table><thead><tr><td>Hypotheses</td><td>Standardized coefficient</td><td>SE</td><td>CR</td><td>Supported</td></tr></thead><tbody><tr><td>H1: PU→AT</td><td>0.43*</td><td>0.044</td><td>9.855</td><td>Yes</td></tr><tr><td>H2: PEOU→AT</td><td>0.381*</td><td>0.037</td><td>10.208</td><td>Yes</td></tr><tr><td>H3: PEOU→PU</td><td>0.349*</td><td>0.038</td><td>9.063</td><td>Yes</td></tr><tr><td>H4: FC→AT</td><td>0.305*</td><td>0.041</td><td>7.357</td><td>Yes</td></tr><tr><td>H5: FC→PEOU</td><td>0.311*</td><td>0.045</td><td>6.871</td><td>Yes</td></tr><tr><td>H6: SC→AT</td><td>0.02</td><td>0.054</td><td>0.367</td><td>No</td></tr><tr><td>H7: AT→IT</td><td>0.266*</td><td>0.037</td><td>7.211</td><td>Yes</td></tr></tbody></table> </ephtml> </p> <p>2 Note: *p < 0.001.</p> <hd id="AN0161687280-17">Discussions</hd> <p>In the context of the COVID19 and the subsequent lockdown imposed all over, education as a sector suffered due to abrupt and sudden closure. The study examined the acceptance of online/virtual learning environments by teachers/instructors in India. However, since online education's emphasis came as a knee-jerk reaction to the pandemic situation, it did not find the preparedness by colleges, teachers, and students adequate (Bao, [<reflink idref="bib5" id="ref62">5</reflink>]; Basilaia & Kvavadze, [<reflink idref="bib6" id="ref63">6</reflink>]; Rapanta et al., [<reflink idref="bib33" id="ref64">33</reflink>]). Hence, a study of all the probable limitations towards online education was necessary to initiate the appropriate and timely interventions to prepare and disseminate online education.</p> <p>The study yielded several outcomes. One of the results is that the intention to use an online teaching-learning can be explained using an extended technology acceptance model with the teachers' service conditions. The teachers' attitudes towards using an OTL led to positive behavioral intentions similar to earlier studies (Teo et al., [<reflink idref="bib42" id="ref65">42</reflink>]). A positive attitude towards the behavioral intentions to use technology by teachers can integrate ICT in teaching and learning methodologies (Buabeng-Andoh, [<reflink idref="bib12" id="ref66">12</reflink>]). The relationships of the proposed model for perceived usefulness, perceived ease of use, and attitude towards the use of technology were supported (Rienties et al., [<reflink idref="bib34" id="ref67">34</reflink>]; Teo et al., [<reflink idref="bib42" id="ref68">42</reflink>]; Teo & Zhou, [<reflink idref="bib43" id="ref69">43</reflink>]). The results were consistent with previous studies using TAM for predicting the intention to use (Venkatesh et al., [<reflink idref="bib47" id="ref70">47</reflink>]). Perceived ease of use was a predictor of attitude towards use. It significantly affects teachers' attitudes towards OLE's use, with the standardized path coefficient being 0.381. Teachers' attitudes towards using OLE were positively influenced by the technology's perceived usefulness, thus contradicting the earlier study (Yuen & Ma, [<reflink idref="bib52" id="ref71">52</reflink>]). Perceived usefulness was a strong predictor of teachers' attitude towards OLE's use with a significant positive effect on the teacher's attitude. The significant path coefficient was the highest with 0.43, indicating that perceived usefulness is the most important for teachers to form a positive attitude for OLE use. Perceived ease of use was significant in predicting OLE's perceived usefulness for teachers conversant with earlier studies (Li et al., [<reflink idref="bib23" id="ref72">23</reflink>]; Yuen & Ma, [<reflink idref="bib52" id="ref73">52</reflink>]).</p> <p>The study saw facilitating conditions for teachers to positively influence teachers' attitudes towards OTL. Teachers' guidance and assistance in adopting OLE give an added impetus to use the OTL easily. However, the ad-hoc approach in the absence of infrastructures like the internet-equipped workstation and the available platforms for dissemination undoubtedly affects teachers' accountability and engagement in adopting the OTL process. Perceived ease of use positively and significantly impacted facilitating conditions, thus strengthening this norm and adopting OTL by teachers. When facilities and support for adopting and using online teaching-learning and the tools are provided, the teacher/faculty instructors adopt it with ease (Bervell & Arkorful, [<reflink idref="bib9" id="ref74">9</reflink>]). The study supported earlier research results considering learning management systems (Bervell & Arkorful, [<reflink idref="bib9" id="ref75">9</reflink>]). The research introduced new variable service conditions related to the teachers employed with higher educational institutions in India. Service conditions did not influence the attitude of teachers towards the use of OTL. It can be attributed to several factors like the availability of resources and support, and remuneration (Sharma & Jyoti, [<reflink idref="bib36" id="ref76">36</reflink>]). Service conditions did not positively influence the teacher's attitude toward OTL use, and the results were concurrent with earlier studies (Wright, [<reflink idref="bib50" id="ref77">50</reflink>]).</p> <p>Even though there are uniform regulatory policies in force for employment and the service conditions, there still seem to the issues in its implementations and regulatory supervisions resulting in variation in employment patterns. In the absence of grants in aid for the private self-financed institutions, revenue through fees remains the only mechanism to manage the institutions. Teachers, mainly from the self-financed institutions, have an apprehension of losing their employment partly or entirely. They fear that OTL adoption will dramatically reduce the student-teacher ratio as even one teacher can teach many students online. It might be looked at as an opportunity by institutions to reduce their number of teachers to cut their costs.</p> <p>Further, there is also anxiety amongst the teachers; others might copy their content/notes online. Contrary to that, some even fear that there could be copyright violations while curating the courses online. Additionally, some teachers are unease about curating/mapping their courses and handover to the institutions. They feel this complete handover of the online mapped course will be redundant and affect their employment continuation.</p> <hd id="AN0161687280-18">Conclusion</hd> <p>The study explored the teachers' acceptance of online teaching-learning due to force majeure arising from the pandemic. In the wake of physical classes' stoppage, teachers from the undergraduate and postgraduate institutes expressed their willingness and preparedness to adopt online teaching-learning. OTL adoption appears voluntary but was mostly found imposed in instructions and guidelines from the Government of India, respective affiliating universities, and other regulatory bodies from India. The results showed the intention to use online teaching-learning methodologies by the users. The variable of service conditions did not influence the attitude towards using OTL technology. The shifting to an online method is more of a knee-jerk reaction to the pandemic – the teachers' capability to adapt to the OTL shaped their attitude towards online teaching.</p> <p>Starting with an ad-hoc approach towards OTL arising from the pandemic, the situation's worsening led to a more long-term approach towards the OTL and its acceptance by the teachers/faculty instructors. This very contextual attitude of the teachers towards the adoption of OTL has been the sole objective of this study. Teachers from the diverse institutions and disciplines prepared themselves for the OTL either as an alternative or as an institute /peer pressure, or with a genuine inclination towards the new instructional method. Even in haste, institutes have started putting their infrastructure together and are developing a new ecosystem to disseminate OTL. However, the teachers working with self-finance/private institutions are found apprehensive and concerned about continuing their services as those institutes might use online teaching as an excuse to reduce the number of teachers. The probable act of teacher downsizing appears to be constrained towards OTL adoption. Higher education regulatory bodies will have to ensure that the institutions follow the teacher's service condition policies. Further to OTL acceptability, teachers will have to capitalize on the available OTL mechanisms by curating and mapping their curriculum with the online content. 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  Label: Title
  Group: Ti
  Data: Technology Acceptance for Online Teaching-Learning: Perspectives of Teachers from Higher Education in India
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  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Kamble%2C+Aakash%22">Kamble, Aakash</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-6152-302X">0000-0002-6152-302X</externalLink>)<br /><searchLink fieldCode="AR" term="%22Golhar%2C+Devidas%22">Golhar, Devidas</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0001-5131-8092">0000-0001-5131-8092</externalLink>)<br /><searchLink fieldCode="AR" term="%22Kalkar%2C+Parag%22">Kalkar, Parag</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-3768-3621">0000-0002-3768-3621</externalLink>)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Educational+Media+International%22"><i>Educational Media International</i></searchLink>. 2022 59(4):324-340.
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  Label: Availability
  Group: Avail
  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 17
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2022
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22COVID-19%22">COVID-19</searchLink><br /><searchLink fieldCode="DE" term="%22Pandemics%22">Pandemics</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Technology%22">Educational Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+Learning%22">Electronic Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Attitudes%22">Teacher Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22College+Faculty%22">College Faculty</searchLink><br /><searchLink fieldCode="DE" term="%22Value+Judgment%22">Value Judgment</searchLink><br /><searchLink fieldCode="DE" term="%22Usability%22">Usability</searchLink><br /><searchLink fieldCode="DE" term="%22Affordances%22">Affordances</searchLink><br /><searchLink fieldCode="DE" term="%22Intention%22">Intention</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22India%22">India</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1080/09523987.2022.2153989
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0952-3987<br />1469-5790
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The sudden outbreak of the COVID-19 pandemic resulted in a transition to an online teaching-learning (OTL) methodology, forcing India's institutions to adopt it. The present study investigates OTL's acceptance by faculty instructors/teachers employed in India's higher educational institutions using the technology acceptance model (TAM). A survey of 433 respondents studied the intention to use OTL by teachers. The study considered India's higher educational institutions and utilized web-based questionnaire survey methods for collecting the responses. The study found support for OTL's perceived usefulness and the perceived ease of use, facilitating conditions to be significant determinants for attitude towards the use of technology by users. The study introduced service conditions related to the faculty instructor/teacher's employment in the higher educational institutions and its bearing on their work routine. The study did not find service conditions as a significant determinant of attitude towards using OTL technology. The results present evidence of a valid model to predict technology acceptance among India's teachers.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2023
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1377034
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      – Type: doi
        Value: 10.1080/09523987.2022.2153989
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 17
        StartPage: 324
    Subjects:
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: COVID-19
        Type: general
      – SubjectFull: Pandemics
        Type: general
      – SubjectFull: Educational Technology
        Type: general
      – SubjectFull: Electronic Learning
        Type: general
      – SubjectFull: Teacher Attitudes
        Type: general
      – SubjectFull: College Faculty
        Type: general
      – SubjectFull: Value Judgment
        Type: general
      – SubjectFull: Usability
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      – SubjectFull: Affordances
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      – SubjectFull: Intention
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      – SubjectFull: India
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      – TitleFull: Technology Acceptance for Online Teaching-Learning: Perspectives of Teachers from Higher Education in India
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