Exploring online education constraints in agricultural sciences: Experiences from teachers and students at Pjtau, Telangana, India

Introduction

The rapid integration of Information and Communication Technology (ICT) into the education system, particularly through platforms such as SWAYAM, Swayam Prabha, e-PG Pathshala, and institutional tools like Zoom, Webex, TCS-iON, Google Classroom, and WhatsApp, has significantly transformed the teaching-learning process in higher education institutions. While these digital platforms have played a crucial role in ensuring the continuity of education, particularly during and after the COVID-19 pandemic, the transition to online learning has not been without challenges. The National Agricultural Higher Education Project (NAHEP) has also played a vital role in strengthening the digital infrastructure in agricultural universities, ensuring that students and faculty are equipped with the necessary technological competencies to thrive in a blended learning environment. This evolving educational paradigm has highlighted the importance of integrating technology into teaching practices, fostering flexible, accessible, and student-centric learning experiences. PJTAU Teachers, students, and researchers-key stakeholders in the educational ecosystem-have encountered a range of constraints in effectively adapting to and participating in online teaching and learning. These constraints arise from technological limitations, infrastructural inadequacies, and personal and institutional readiness for digital learning. Understanding the specific constraints faced by respondents, is essential for improving the quality, accessibility, and inclusivity of online education. In this context, it becomes imperative to systematically assess the challenges experienced by respondents to identify critical areas requiring intervention, thus ensuring that www.extensionjournal.com digital learning platforms are optimized to meet the needs of all users. The insights gathered from such assessments can guide educational institutions and policy makers in developing effective strategies to enhance the overall online learning experience while addressing the barriers that hinder seamless participation.

Objective of the study: To identify constraints faced by teachers and students in PJTAU during online teachinglearning process.

Review of literature

Amita (2020) [3] in a study on "e-learning experience of students" concluded that poor internet connectivity problem was ranked I followed by problem in choosing best source due to flooding of information (Rank II), nonavailability/affordability of e-learning resources like laptop/desktop at home (Rank III), lack of adequate technical skills (Rank IV) and electricity problem (Rank V) as barriers in online learning. Singh et al. (2020) observed that lack of face-to-face interaction with teachers, inconvenience in clearing their doubts, the level of distraction while online learning as compared to classroom were the major challenges faced by students in online education. Haider and Al-Salman (2020) [10] found that prolonged use of e-learning tools was associated with numerous health issues, including tiredness, boredom, nervousness and tension, in addition to having an adverse effect on their sleep patterns. Ahammad (2021) [1] in a study on "Online learning initiatives" reported that less than one-fourth of participants claimed network problems (22.00%), followed by technical problems (14.00%), lack of knowledge about onlinelearning platform (13.00%), expensive (11.00%), understanding problems (9.00%), equal proportion of 8.00 percent each claimed online learning content is not appropriate according to the needs of learners, lack of advance software, security problems and lack of time flexibility (7.00%) as barriers while using online learning platforms. According to Dhivya and Rajasekaran (2021) [7] the main obstacle to online learning was a lack of connectivity, including network issues, slow data, etc. The findings indicate that a significant proportion of students, particularly those from remote areas, struggle with the digital divide and unequal access to the internet. The absence of devices, inadequate learning environments, difficulty to focus on screens, little to no face-to-face interaction, and fear of using new technology were placed second, third, fourth, fifth, and sixth, respectively. Muthuprasad et al. (2021) [14] in a study on "Students' perception and preference for online education in India" concluded that lack of connectivity was ranked I followed by data limit (Rank II), data speed (Rank III), little/no faceto face interaction (Rank IV), intense requirement for selfdiscipline (Rank V), lack of device (Rank VI), poor learning environment (Rank VII) and technophobia (Rank VIII) as constraints in online learning. Almaiah et al. (2020) [2] identified critical challenges and factors influencing the e-learning systems during this COVID-19 pandemic. The three main challenges identified were change management issues, e-learning system technical issues and financial support. Respondents stated that the critical factors that needs to be addressed and should be taken in the future plans were technological factors, e learning system quality factors, trust factors, self-efficacy factors and cultural aspects. Dhawan (2020) [6] conducted strengths, weaknesses, opportunities and challenges (SWOC) analysis of online learning in this time of global pandemic. Reported weaknesses were technical difficulties, learner's capability and confidence level, time management, distractions, frustration, anxiety and confusion and lack of personal/physical attention. Challenges were unequal distribution of ICT infrastructure, quality of education, digital illiteracy, digital divide and technology cost & obsolescence. Gautam (2020) [9] reported that online learning has its own set of positives and negatives. The disadvantages of online learning were inability to focus on screens, technology issue, lack of teacher's training and increase in screen time. Teachers had very basic understanding of the technology and sometimes they did not even have the necessary resources and tools to conducts online classes. To combat this, training of teachers with the latest technology updates is necessary so that they can conduct their online classes seamlessly. Hasan and Khan (2020) [12] reported poor network and connectivity as the most disliked elements of online learning. Adding to it, lack of interaction, distractions and one-sided learning were mentioned as its disadvantages. Online safety and security issues were not addressed and disabled students experienced teachers' negligence and lack of support. According to Haron et al. (2021) [11] there were five key problems that the students had to deal with online learning: network and bandwidth restrictions, a lack of engagement, difficulty learning technical subjects, the new normal for class interaction, and stress. The main issue with online teaching and learning is network and bandwidth limitations. Naik et al. (2021) [15] through a study on online teaching and learning during lockdown confirmed that the traditional chalk and talk methodology is often better than online sessions. Lack of facilities, infrastructure, technical tools and the internet access are the major drawback for conducting online sessions. During online classes many faculties often faced problems in teaching special subjects which need face to face interaction. Few students expressed that for practical and problematic subjects, online teaching was often difficult to understand. According to Saha et al. (2022) the teachers' most significant barriers were difficulty with practical work, followed by difficulty supervising students and inadequate feedback. Less student -teacher interaction, less usefulness for assessment, lower student involvement, minimal student interest, poor network connectivity, along with a lack of proper regulations were the other apparent difficulties for teachers.

Research Methodology

An Ex-post facto research design was adopted for the study, since the variables chosen for the study have already occurred, researcher does not have direct control on www.extensionjournal.com influencing (independent) variables. The study was conducted in Professor Jayashankar Telangana Agricultural University in Indian State of Telangana. Teachers and students, who have been involved in the teaching-learning process through online teaching-learning platforms during the first and second semesters of 2020-21 were considered for the study. Data was collected from a total of 80 teachers and 240 students. Proportionate random sampling was followed to select the teachers who taught B.Sc. (Hons.) Agriculture, among six Agricultural colleges of the PJT Agricultural University. Six (6) agricultural colleges of Professor Jayashankar Telangana Agricultural University, which offered courses in B.Sc. (Hons.) Agriculture, through online teaching-learning platforms during the first and second semesters of 2020-21 were considered for the study. The colleges are (1) College of Agriculture, Rajendranagar (2) Agricultural college, Aswaraopet (3) Agricultural college, Jagtial (4) Agricultural college, Palem (5) Agricultural college, Warangal, and (6) BJR Agricultural College, Sircilla. This study aimed to know, the constraints faced by the respondents during the online teaching learning process. The instrument designed to measure the experiences of teachers and students, underwent a reliability analysis using Cronbach's alpha, which yielded a reliability coefficient of 0.82, indicating a high level of internal consistency. From the identified constraints during pretesting, top ten constraints were finalised and the respondents were asked to rank these statements according to their priority. Then, based on Garrett's score card, mean score is calculated and ranking was done. The instrument was administered to 80 respondents which included (47) Assistant professors, ( 14) associate professors and (19) professors, and 120 students of 2019 admitted batch and 120 students of 2020 admitted batch, total students constituting 240. The Garrett Ranking technique is a widely used statistical tool for ranking factors or variables based on respondent preferences. It converts ranks into scores using a specific formula and a standard table of values developed by Henry Garrett and Woodworth (1969).

Formula for Garrett Ranking

The percentage position (P) of each rank is calculated using the formula: P={100(Rij-0.5)}/Nj Where: Rij = Rank assigned to the i th factor by the j th respondent. Nj = Total number of factors ranked by the j th respondent. The percentage position is then converted into scores using a standard Garrett table. The total score for each factor is computed by summing up the scores assigned by all respondents. Finally, the average score is calculated, and factors are ranked based on their average scores.

Aspects of Garrett Ranking

Calculation method: Converts ranks into percentage positions and assigns scores using a pre-defined table (Garrett Table ).

Purpose: Focuses on ranking factors based on their perceived severity or importance as judged by respondents.

Precision: Provides a more nuanced ranking by converting qualitative preferences into quantitative scores.

Flexibility: Can handle varying numbers of ranked items across respondents and still produce comparable results.

Applications: Widely used in social sciences, agriculture, psychology, and decision-making studies for detailed analysis.

Output format: Produces average scores that allow for easy comparison of factors based on their relative importance.

Advantages of Garrett Ranking

1. It accounts for the seriousness or impact of factors from the respondent's perspective, unlike simpler ordinal ranking methods. 2. The use of percentage positions and conversion tables ensures consistency across varying datasets.

Limitations of Garrett Ranking

Garrett Ranking requires additional steps like converting ranks to percentages and using predefined tables, making it more complex than simpler ranking techniques like standard ordinal ranking or frequency-based methods.

Steps to determine the severity of constraints 1. Collection of rankings: respondents rank the constraints (or factors) based on their perceived severity or importance. Here, teachers and students were given a set of 10 items, and asked the respondents to rank according to their priority. 2. Calculation of percentage position: By using the formula for percentage position (P) given, P={100(Rij-0.5)}/Nj Where: Rij = Rank assigned to the i th factor by the j th respondent. Nj = Total number of factors ranked by the j th respondent.

Conversion to Garrett scores:

The percentage positions are then converted into Garrett scores using a predefined Garrett Conversion Table . This table provides scores corresponding to specific percentage positions.

Summation of scores:

The scores for each constraint are summed across all respondents to calculate the total score for each constraint.

Calculation of Average scores:

The average score for each constraint is computed by dividing the total score by the number of respondents who ranked it: Average score = (Total Score)/(Number of Respondents) 6. Ranking Based on Average Scores: Constraints are ranked based on their average scores, called as mean score, with higher scores indicating greater severity.

Key features of Garrett ranking

• The use of percentage positions ensures that variations in the number of items ranked by different respondents do not affect comparability. www.extensionjournal.com

• By converting ranks into scores, Garrett Ranking provides a more nuanced measure of severity compared to simple ordinal ranking.

This method is widely used in studies involving prioritization or constraint analysis in fields like agriculture, social sciences, and management research.

Results and discussion

Summary and Conclusion

To summarise, Teachers encountered a wide array of challenges while transitioning to digital and blended learning environments. One of the most pressing issues was technical difficulties, including unstable internet connectivity and software incompatibility, which often disrupted online classes. Closely related to this was digital incomprehensibility, where teachers struggled to understand and navigate the multitude of online platforms and educational technologies without sufficient training and prior exposure. Maintaining student engagement also emerged as a major hurdle, with students often disengaging due to distractions, low motivation, or passive learning methods. Teachers reported that their workload increased significantly, with the need to redesign lesson plans for digital delivery, monitor online assignments, and provide individualized support to students.

Compounding this was the non-availability of suitable assessment tools, which made evaluating student progress difficult in virtual settings. Teachers also faced challenges in accurately assessing students' understanding, particularly in the absence of in-person cues such as facial expressions and body language. Additionally, many students hesitated to actively participate in online discussions, further complicating teachers' ability to foster interaction and collaboration. The lack of face-to-face interaction weakened teacher-student rapport and limited opportunities for spontaneous feedback. Teachers also had to continuously adapt to evolving digital tools and pedagogical strategies, leading to professional fatigue. Finally, the time required for reviewing and grading digital assignments was significantly higher than for traditional assessments, adding further strain to teachers' already heavy workload

Strategies for Addressing

Increased Workload for Teachers (Rank X):

Develop a dedicated support mechanism for seamless digital and online teaching. Train teachers accordingly to ease the workload.

Summary of Constraints Faced by Students

Students also faced numerous barriers in adapting to online learning environments, many of which were deeply interconnected with socioeconomic and infrastructural challenges. The most prominent constraint was the lack of access to proper digital devices, with many students forced to share devices with siblings or use outdated equipment unsuited for online learning. Poor internet connectivity ranked as the second most significant constraint, particularly in rural areas where stable internet is scarce. Many students also reported inadequate technical skills, making it difficult to navigate learning platforms, submit assignments, or troubleshoot minor issues. The shift to online learning significantly reduced student-teacher interaction, depriving students of the timely guidance and personalized support available in traditional classrooms. Online assessments and examinations became another major source of stress due to unfamiliar formats, technical difficulties, and concerns about fairness. Furthermore, lack of motivation for selflearning emerged as a common challenge, with students struggling to stay focused without external structure and peer support. Mental stress and cognitive fatigue increased due to prolonged screen exposure, isolation, and the cognitive overload associated with digital learning environments. Additionally, students were exposed to numerous distractions at home, ranging from household noise to competing responsibilities, which further impeded their concentration. Many students also found the noninteractive teaching methods used in online classes unengaging, leaving them passive participants in their learning. Finally, difficulty in understanding concepts arose from the absence of hands-on activities, peer discussions, and immediate feedback, making complex topics harder to grasp.

Solutions for Addressing

Difficulty in Understanding Concepts (Rank X):

Course videos could be kept brief (20 minutes or less) with the provision of transcripts to support comprehension, particularly addressing dialectal differences and language barriers.

Limited Interaction with Teachers (Rank IV):

Universities could establish dedicated digital learning cells on campus to provide individualized academic support and facilitate virtual office hours where students can seek direct guidance from faculty.

Lack of Motivation for Self-Learning (Rank VI):

Personalized learning experiences could be introduced to foster student motivation, with particular emphasis on supporting specially-abled students pursuing agricultural courses. 6. Distractions at Home (Rank VIII): Universities could mandate regular teacher-parent discussions to ensure parents understand academic expectations and the need for a conducive learning environment at home. Standardized templates for online assessments could be introduced to enhance transparency and reduce uncertainty, ensuring fair evaluation processes and reducing assessment-related stress. 9. Non-Interactive Learning Methods (Reduced Attention Span) (Rank IX): Interactive and engaging content could be designed to cater to various learning styles. Additionally, incentives such as allocating 10% of class marks for participation in online discussions or forums could encourage active engagement.

Mental Stress and Cognitive Fatigue (Rank V):

Universities could appoint psychology consultants or counsellors to offer professional support to students, helping them manage stress, maintain mental wellbeing, and develop coping strategies.

Concluding Remarks:

The transition to online education in agricultural courses highlighted several challenges for both teachers and students. Teachers faced technical difficulties, digital incomprehensibility, increased workloads, and limited means to assess student understanding effectively. Simultaneously, students grappled with poor internet connectivity, lack of proper devices, limited teacher interaction, low self-motivation, and cognitive fatigue. These constraints collectively affected teaching efficiency and learning outcomes.

To overcome these barriers, institutions must invest in robust infrastructure, provide regular technical and pedagogical training, establish standardized assessment tools, and foster interactive learning environments. Personalized learning experiences, virtual office hours, and better student-teacher engagement can enhance student involvement. Additionally, psychological support, parental sensitization, and hybrid teaching models would create a more inclusive and adaptive system. By addressing these issues holistically, agricultural education can evolve into a more resilient, student-centered system that balances technology with human connection, ensuring both learning continuity and quality.

Conflict of interest:

Authors doesn't have any conflict of interest.

Funding:

The study is funded by ICSSR, New Delhi.

Acknowledgements: My heartfelt gratitude to all the teacher and student respondents who took their invaluable time in recording their experiences and were available to me, when I needed clarifications. I specially thank Associate

Acknowledgement

www.extensionjournal.com deans of all the agricultural colleges, for facilitating the data collection.

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