4.1. Participant Selection and Recruitment
Participants were asked about their experiences with ChatGPT or similar tools, and how they saw these technologies in relation to their educational practices. The descriptive analysis summarised the main traits of the quantitative data, providing an overview of response tendencies, while thematic analysis of open-ended questions revealed patterns and themes regarding the integration of generative AI technologies into higher education, as well as suggestions for how university should build their strategic plans. The mix of quantitative and qualitative data helped to provide a well-rounded understanding of stakeholder perceptions, allowing us to identify potential needs, recommendations, and strategies for AI policy development in teaching and learning at universities, ensuring the ethical and advantageous use of these technologies.
One survey question looked at participants’ opinions on AI policy: whether students, teachers, and staff believed that there should be established plans and a dedicated policy for AI technologies and their use within the university. The results were encouraging, showing a strong consensus that institutions should indeed have such plans (students: M = 4.50, SD = .85; teachers and staff: M = 4.54, SD = .87; responses were based on a 5-point Likert scale, with “5” indicating “Strongly agree”). Responses to other questions further indicated that students and teachers are aware of the possible advantages and disadvantages associated with AI technologies. They also acknowledged the potential of using GenAI for guidance, personalised feedback, enhancing digital skills, and improving academic performance, along with its benefits of offering anonymity in student support services. However, apprehensions about excessive reliance on AI, reduced social engagement, and a possible impediment to the cultivation of generic skills were also expressed.
Sometimes, either the benchmark creator or the relevant community will establish a leaderboard, displaying ranked scores for each tested model, facilitating easier comparison. Such leaderboards might also feature a human baseline score, derived from the average scores of human participants. This addition can offer context, helping users appreciate the model’s performance. It is not uncommon for models to surpass the average human score in many benchmarks [17].
4.2. Integration Design and Setup
ChatGPT: Chat Generative Pre-Trained Transformer (ChatGPT) is an open ‘AI’ instrument that offers free access to contents. It creates dialogue using reinforcement Learning with human feedback (RLHF), that compares human demonstrations and preference to guide a model toward a target character or behaviour. ChatGPT has several models that were trained on huge data capacity written by humans in conversation nature, and therefore give human-like responses in written structure.
The integration of ChatGPT into the philosophy course can produce several significant outcomes:
- The dynamic nature of the assignment, combined with real-time feedback from ChatGPT, can foster increased student engagement.
- The requirement to constantly defend and structure arguments in debates allow students to develop analytical and argumentative skills.
- Through the peer review component, students can benefit from diverse perspectives, in which the collaboration among peers can also enhance collective learning.
- The ChatGPT transcripts and reflections provide the educator with a greater understanding and insight into their students’ learning. This also would enable tailored classroom sessions to address specific issues based on students’ demonstrated understanding of philosophical stances [18].
Padlet: Is an educational enterprise that provides cloud-based real-time ‘padlets’. The padlets are virtual bulletin boards that users used to upload, organize, and share educational, organizational, social contents, and so on [19].
The survey consists of open-ended questions, exploring in-depth thoughts from the participants on the teacher’s integration of two particular m-learning tools, Padlet and ChatGPT, in their introductory lessons.
1. What are you happy about in our English class?
2. What are you NOT happy about in our English class?
3. Do you have any concerns about our English class?
From various survey tools, such as paper and pencil, Survey Monkey and Survey builder, this study pioneeringly utilized Padlet. Once users add words or pictures on Padlet, they are automatically saved and, as required, they can be generated in the forms of PDF or Excel spreadsheet which can be exported. Then researchers can analyse the data from the output [20].
The other major factor in relation to integration and incorporation of digital technology in the classroom is lack of technical support. In some institutions where digital facilities are available, teachers complained about lack of technical support. In a recent most of ELT teacher participants pointed out that there is no adequate technical support staff when teachers need them. Specifically, they stated that schools do not have full time technicians, or they are busy with other responsibilities. Ghanaian teachers also supported this view that absence of technical support especially technician discourages integration of technology in the classroom because sometimes both software and hardware repair are required for the digital devices in the classroom [21].
4.3. Training and Familiarization
Training and familiarization for ChatGPT and Padlet involved several key steps to ensure effective integration and usage among engineering students. Firstly, faculty members underwent comprehensive training sessions to familiarize themselves with the functionalities and capabilities of both ChatGPT and Padlet, including how to customize settings to suit the specific needs of engineering education. These training sessions also emphasized best practices for incorporating these tools into reading and writing activities within engineering coursework. Following faculty training, students participated in orientation sessions where they were introduced to ChatGPT and Padlet interfaces, guided through hands-on exercises to explore the features and functionalities of each platform, and provided with resources and tutorials for independent usage. These sessions aimed to build students' confidence and competence in utilizing ChatGPT for reading comprehension tasks and Padlet for collaborative writing assignments, ensuring seamless integration into their learning experiences. Additionally, ongoing support and troubleshooting mechanisms were established to address any technical issues or queries that arose during the implementation phase, fostering a supportive learning environment conducive to enhancing reading and writing proficiency among engineering students.
4.3.1. Training Sessions for Faculty and Students
There are several ‘AI’ instruments and platforms that are emerging, and are now been utilized in educational environment. They are usually software-dependent, hence; technical skill and digital literacy are required for their functions in enhancing teaching, learning, and research. The features such instruments are still emerging with new specifications. The instruments provide functions such as document writing, web search, note-taking, speech-recognition, design, image-making, assessment, presentation, verification, translation, summary, quizmaking, task scheduling, feedback and survey, research writing, and so on. Refers to responses obtainable from ‘AI’ instruments. In teaching and learning process, AI instruments support functions such as text edition, text prediction, presentation design, image-making, analysis and budget, scheduling of tasks, review and summary of articles. The resources lack updates on current information regarding process. They are usually few years late to the existing process. AI contents are usually considered as a guide.
Artificial intelligence (AI) is effective in breaking down complex tasks when used in several sectors, teaching and learning is not an exception. Several enterprises are currently developing AI-powered digital tools and platforms that provide academic services such as online interaction, document writing, translation, assessment, verification, evaluation, analysis, proctoring, feedback, research writing, and so on. The global adoption of AI in education is changing the process of teaching, learning, and research. Therefore, notable functions of AI-powered instruments in teaching and learning include the following; text prediction, text edition, translation, summarization, grammar check, plagiarism detection, assessment and metrics, learning management system, chatbot, transcription, online discussion and classroom, lesson planning, audio-visual interaction, communication, gamification, staff and student scheduling, professional development, professional and behaviour management, maintenance, transportation, academic research, safety and security, so on [22].
4.3.2. Familiarization with ChatGPT and Padlet Interfaces
Familiarization with the ChatGPT and Padlet interfaces was conducted through structured orientation sessions designed to acquaint engineering students with the functionalities and navigation of both platforms. During these sessions, students were provided with hands-on demonstrations of the features available on the ChatGPT interface, including how to input prompts, generate responses, and interpret outputs. They were also guided through the Padlet interface, learning how to create collaborative boards, post content, and interact with peers. Additionally, students were introduced to the various tools and options within each platform, such as formatting options on Padlet and customization settings on ChatGPT, to empower them to personalize their user experiences. Practical exercises and interactive demonstrations allowed students to explore the capabilities of both platforms in a controlled environment, fostering confidence and proficiency in utilizing ChatGPT and Padlet for their reading and writing tasks. Through these familiarization sessions, students gained the necessary skills and knowledge to effectively integrate these tools into their learning processes, enhancing their reading and writing proficiency in engineering education.
4.4. Implementation Procedures
In the second part of this chapter, we will explore the potential of new technologies in ELT classrooms. We will discuss the implementation processes, examples, and suggestions for emerging technologies we described in the previous section. Furthermore, we will present other available technologies that can enhance language skills development in reading, writing, speaking, listening, grammar, and vocabulary. By the end of this section, you will have a better understanding of how to integrate these technologies effectively in your language teaching practice.
4.4.1. System Design
Catering to non-technical users such as engineering college teachers and students, we integrate the features discussed in previous sections into a unified system with a graphical user interface. The prompts and API calls are managed at the system backend, while a user-friendly and straightforward interface is designed for ease of use. On the left side of the interface, users can easily set their requirements, with each previously mentioned feature incorporated. The output reading passages and exercise questions are displayed on the right. These text areas are editable, allowing teachers to further modify the generated content to create a final version of exercises suitable for student practice.
4.4.2. ChatGPT for Reading Exercise Generation
Utilizing the impressive capabilities of ChatGPT, we manually design input prompts to generate high quality reading comprehension passages without the need for fine-tuning or additional control methods. In this study, we produce textual content in two settings: zero-shot and one-shot, which allow us to control the output to varied degrees. In the zero-shot setting, we instructed ChatGPT to be a helpful learning assistant capable of generating high-quality reading passages in the system prompt.
We provided customized requirements within the conversation prompt, including length, genre, difficulty level, and topics. In addition to creating reading passages from scratch, teachers often source content from the web or other materials and seek to adapt them into suitable reading passages for students. Thus we added an extra requirement, a referenced passage, in the one-shot setting. We also generate questions and corresponding answers for given passages using appropriate prompts. We set the number of questions, the number of options per question, and the question type for customization in the input prompt. ChatGPT can generate exercise questions based on either a passage it previously created or a passage provided by users. Moreover, an extra toxicity check is applied before the generated exercises are made available to teachers and students [23].
4.4.3. Padlet for Writing Generation
Focusing on the current writing context and the needs of the learners, the synthesis of a more productive, collaborative and inspiring writing lesson is indispensable. Delving into process writing, this approach is defined as a “non-linear exploratory and generative process”, setting the basis for a learning experience based on the discovery of learning, knowledge and inner world. Thoroughly illustrates it in four basic phases: “planning, drafting, revising and editing” while through this path, there is the opportunity of a back and worth notion following a recursive procedure. In this non-linear movement, the ideas are freely expressed, enriched, developed, shared and reconsidered while the main emphasis is given on meaning and fluency as accuracy is deprioritized. In this vein, activities based on open discussions and brainstorming are encouraged while model texts and guided tasks are avoided. Consequently, a creative environment of multiple interpretations, various voices is shaped, impeding the stress of correctness and the fear of perfection. In this approach, the focus is on the process rather than on the flawless final product.
Furthermore, the role of collaboration and communication is underlined, as group and pair-work activities are promoted. Moreover, peer-assisted writing , which allows the students to create cooperatively drafts, plans, notes, and peer-feedback, according to which the learners evaluate each other’s performance and share their knowledge and comments, are important parts of this approach. All these features fill the ELT class with respect, acceptance, security and warmth, building the most appropriate basis for a fruitful lesson full of motivation, inspiration, cooperation and freedom. Thus, this would be the most appropriate approach not only for the needs of these learners but also for a creative writing class.
Last but not least, considering the immense contribution of technology to learners’ improvement, it is undeniable that without the integration of technology, the lesson cannot be taught powerful, effective and thought-provoking. In this light, a writing lesson based on process-orientation integrating technology has been synthesized [24].
4.5. Data Collection Methods
4.5.1. Data Collection Methods for ChatGPT
The ELT were created to collect information regarding the opportunities and challenges of ChatGPT in teaching research. The researchers developed a comprehensive set of ten questions to discuss the various effects or influences that ChatGPT in ELT teaching research. Follow-up questions such as “What do you mean?” and “Can you clarify, please?” were used to elicit additional information and stimulate more discourse. Because the sample involved participants from different countries, English language medium was adopted for focus-group discussions. Every participant spoke English quite well, regardless of where they were from or what their mother tongue was. The interviewer who functioned as the focus group discussions moderator ensured that all participants were involved by questioning about their perspectives on the study’s goals. This was done to ensure that all opinions were heard and to avoid the dominance of focus group discussions by a few persons, which is a common concern with focus group processes. Despite this, the participants in this study had a lot in common. They were all academic researchers, and the interviewer was able to manage the focus group discussions satisfactorily since the ChatGPT influence was constant in various ways. All participants were guaranteed anonymity and privacy, and their participation was completely voluntary. Voice recordings of the sessions were recorded in order to obtain complete information from the focus group discussions. Every session lasted nearly an hour. Participants provided informed consent before to each focus group discussions session. The usage of pseudonyms and codes ensures that the data is reported in an anonymous manner [25].
Table 1: Summarizes the Key Aspects of the Data Collection
|
Aspect
|
Description
|
|
Purpose
|
To explore opportunities and challenges of integrating ChatGPT in ELT teaching research.
|
|
Data Collection Method
|
Focus group discussions with a set of ten questions and follow-up inquiries.
|
|
Language Medium
|
English, chosen for inclusivity among participants from diverse linguistic backgrounds.
|
|
Participants
|
Academic researchers with proficient English language skills, ensuring effective communication.
|
|
Moderator's Role
|
Facilitated discussions, ensured equitable participation, and managed group dynamics effectively.
|
|
Commonalities
|
Despite diverse origins, participants shared common ground as academic researchers, facilitating cohesive discussions.
|
|
Anonymity and Privacy
|
Guaranteed for all participants, with voluntary participation and pseudonymous data reporting.
|
|
Data Collection
|
Voice recordings of sessions, lasting approximately one hour each, to ensure comprehensive data capture.
|
|
Informed Consent
|
Obtained from participants before each focus group session, ensuring ethical conduct and participation.
|
4.5.2. Data Collection Methods for Padlet
The study was conducted over 12 weeks, from mid-August to the end of November 2018. There were two types of data gathered and used for this study: 1) survey questionnaire data and 2) interview data. All the 60 participants were asked to complete the survey questionnaire on their perception of using Padlet as a learning tool for English writing at the end of week 12. Six participants were randomly selected for a focus group interview based on their willingness to participate. The focus group interview took 30 minutes to get an in-depth understanding of their perception in using Padlet as a learning tool for English writing. All of the interviewed participants were named as Participant A, Participant B, Participant C, Participant D, Participant E and Participant F. The quantitative data was keyed into SPSS (Statistical Package for Social Sciences) and analyzed using descriptive analysis. The qualitative data then was analysed based on interview content [26].
Table 2: Students’ perceptions of using Padlet as a learning tool
|
Statement
|
Mean
|
Std. Deviation
|
|
I like to see my friends’ comments on Padlet
|
3.38
|
0.524
|
|
Padlet enables me to share ideas with my friends
|
3.60
|
0.494
|
|
Because of Padlet, my class members are able to reach an agreement
|
3.57
|
0.722
|
|
I developed new ideas from the activities on Padlet
|
3.62
|
0.666
|
|
I learned new concepts from the other posts on Padlet
|
3.65
|
0.860
|
|
I learned through collaborative learning with Padlet
|
3.70
|
0.809
|
|
The materials posted on Padlet were clear
|
3.50
|
0.792
|
|
The materials posted on Padlet were useful
|
3.52
|
0.792
|
|
The activity on Padlet was challenging
|
3.30
|
0.720
|
|
I got ideas on the advantages and disadvantages of ICT from the materials posted on Padlet
|
3.20
|
0.777
|
|
Overall
|
3.50
|
0.476
|
4.5.3. Usage Logs of ChatGPT and Padlet
ChatGPT:
Instant Feedback: One of the biggest advantages of using GPT chat in language learning is the instant feedback that it provides. Unlike traditional language learning methods where feedback can take a while to arrive, GPT chatbots can provide feedback immediately after a response is given. This allows learners to correct their mistakes in real-time and to continue learning without losing momentum.
Personalised Learning: GPT chatbots can be programmed to personalise the learning experience for each learner. Based on the learner's level and progress, the chatbot can provide tailored lessons and exercises that are relevant to their current level. This personalised approach can help learners stay motivated and engaged, as they are constantly challenged without feeling overwhelmed.
Accessible and Convenient: GPT chatbots are accessible and convenient to use. Learners can use them anytime, anywhere, as long as they have an internet connection. This makes language learning more accessible to people who may not have the time or resources to attend traditional language classes. Additionally, learners can use GPT chatbots at their own pace, without feeling rushed or pressured.
Realistic Conversations: GPT chatbots are designed to simulate realistic conversations between native speakers. This allows learners to practise their language skills in a natural and authentic way. By engaging in conversations with the chatbot, learners can improve their speaking, listening, and comprehension skills. This can help learners feel more confident when they have to use the language in real-life situations.
Time-efficient: GPT chatbots can help learners save time. Since learners can access the chatbot anytime, they can fit language learning into their busy schedules. Additionally, GPT chatbots can help learners learn faster. By providing instant feedback and personalised lessons, learners can progress at a faster pace than they would with traditional learning methods [27].
Padlet:
All the factors mentioned above make it an absolute necessity to redesign students’ learning experiences according to their relevant needs. In this context using collaborative platforms, e.g. Padlet, Google Classroom, or an internal university platform may be the key. First of all, collaborative platforms provide students with constant access to all the course materials, by placing the links either to the materials themselves or to a Google Drive containing them. Furthermore, students can post their works (texts, audio and video recordings) in order to get teachers’ feedback or peer reviews. Thus, a balance between synchronous and asynchronous learning can be achieved, as far as those students who could not for some reason attend a lesson have almost the same opportunities to share their ideas as those who could attend. Finally, all the links to interactive quizzes (using Google Forms, quizizz.com, etc) can also be posted on a padlet wall, thus simplifying the process of assessment.
Using collaborative platforms certainly contributes to this, encouraging students to be more independent in their learning, but at the same time, it demands the development of self-discipline, which a lot of students, especially those with low language competencies, may lack. The reason for that, in its turn, may be either a lack of self-confidence or a lack of interest. In this case, a Padlet wall may become a kind of social network, just for one group of students, creating an atmosphere of involvement, and teamwork, thus arousing curiosity and interest. Sharing ideas, and posting works, that is making them public (unlike sending them directly to a teacher), commenting on peers’ posts, and communicating (e.g., writing invitations and responding to them) may give students a sense of practical application on what was acquired in terms of learning [27].
Padlet (www.padlet.com) provides a variety of templates, including wall, stream, grid, shelf, map, canvas, and timeline. Apart from course materials, tutorials and class projects can also be added to the same Padlet, and students can post and start a discussion with their fellow classmates. This tool would encourage student-to-student and lecturer-to-student interaction. Having had an organised layout for Padlet, it is important to seek feedback on its overall design in terms of quality criteria. The Learning Object Review Instrument (LORI) was coined by as a guide for “eliciting ratings and comments from learning resource evaluators.” The feedback received will be used to improve the current Padlet for future use.
Padlet has a variety of features for lecturers to choose from, including an online bulletin board, a wall, and a canvas, where lecturers can create a wall with a variety of information about their courses, such as ideas, images, videos, links, and documents, and collaborate with their students by sharing. This wall will then serve as a one-stop conversation hub in the classroom. Comparing having many platforms at the same time to sharing a collection of course materials with students in a single platform would help them manage a course better. Students can simply click the Padlet link provided by their lecturer and begin collaborating during class right away [28].
4.5.4. Samples of Student Work from Padlet
Pre-test and post-test were conducted to identify whether there was a significant effect on students’ learning outcomes of writing through collaborative discussion using Padlet-based teaching materials. The first test had been carried out before applying the collaborative discussion using Padlet based teaching materials. The test was assigned before the students achieved some treatments. It is called pre-test. Furthermore, the post-test had been carried out after learning writing through collaborative discussion using Padlet-based teaching materials. The treatments were applied for four appropriate meetings with an adapted semester learning plan. The result of the SPSS using paired Sample T-Test from the pre-test and post-test.
Table 3: Paired Samples Statistics
|
|
Mean
|
N
|
Std. Deviation
|
Std. Error Mean
|
|
Pair 1
|
Pre test
|
1.461
|
45.78
|
35
|
8.621
|
|
Post test
|
1.529
|
58.90
|
35
|
9.035
|
The output in table figures out the pre-test and post-test results of a single sample study in descriptive statistics analysis. For the value of the pre-test, an average learning outcome or mean score of was obtained. While for the post-test score, it was obtained an average value of learning outcomes with a total of 40 students. Therefore, it could be mentioned descriptively that there was a difference in the average learning outcomes before and after applying collaborative discussion using Padlet-based materials in writing. The mean score of pre-test post-test marked the difference.
In addition, to prove whether there was a significant difference or not, the researcher used the calculation of the paired-sample t-test.
Table 4: Paired Samples Correlations
|
|
N
|
Correlation
|
Sig.
|
|
Pair 2
|
Pretest & Posttest
|
35
|
.745
|
.000
|
Table shows the correlation test result that enclosed by the two data. It indicates the relationship between the Pre- Test with Variable post-test. Based on the output written in Tabel, it is found that the correlation coefficient or correlation is equal to .745 with a significance value (Sig.) Of 0.000. This indicates the influence of the collaborative discussion using Padlet-based teaching materials towards student writing outcomes in Mechanical Engineering class [29].
4.6. Assessment Metrics
The integration of artificial intelligence (AI) into education has brought about significant changes in the way assessments are conducted and evaluated. As we enter the AI era, continuous formative assessment, AI-enhanced performance analysis, and the evolving role of teachers in evaluating AI-generated work are reshaping the landscape of educational assessment. This essay explores the impact of AI in assessment and evaluation, highlighting these three critical dimensions. Formative assessment, a crucial aspect of education, focuses on providing feedback to students during the learning process, helping them identify strengths and weaknesses. AI technology has transformed this process into continuous formative assessment by offering real-time, personalized feedback and insights.
AI algorithms analyze students' responses to questions, assignments, and quizzes, generating instant feedback based on their performance. These insights help students identify areas that require improvement and allow them to adjust their learning strategies accordingly. This real-time feedback contributes to enhanced learning outcomes and a deeper understanding of subject matter. AI has also revolutionized performance analysis by enabling the collection and interpretation of vast amounts of data related to student performance. AI-powered learning management systems can aggregate and analyze data from various sources, such as online assignments, tests, and engagement metrics.
These systems can identify patterns and trends, allowing educators to gain a more comprehensive view of individual and class-wide performance. For example, AI can detect when students are struggling with specific topics or skills, enabling educators to adjust their teaching methods and provide timely interventions. AI-enhanced performance analysis goes beyond traditional grade-based assessments to provide a more holistic view of student progress. As AI-generated assessments and evaluations become more prevalent, the role of the teacher is evolving. While AI can provide valuable insights and real time feedback, educators remain essential in guiding the learning process and interpreting the results.
Teachers play a crucial role in designing assessments that align with learning objectives and curriculum standards. They must select or develop appropriate AI-based assessment tools and ensure that the assessment process remains fair and unbiased. Additionally, educators interpret the data generated by AI systems, taking into account the broader context of student performance. Furthermore, teachers have the responsibility of integrating AI-generated insights into their teaching strategies. They can use this information to tailor instruction to individual student needs, identifying areas that require reinforcement and offering additional support where necessary. The teacher's expertise in understanding students' unique learning styles and needs remains invaluable in the AI era [30].
4.6.1. Evaluation Rubrics for Reading Comprehension
The first application to be explored involves its capacity to generate tailored text passages based on a specific topic that usually is relatable to or to the liking of the learner, linked to a designated Common European Framework of Reference for Languages (CEFR) proficiency level. This feature enables EFL teachers to create contextually relevant and level-appropriate reading materials that incorporate new vocabulary seamlessly, making it easier to address the individual needs of learners. Furthermore, ChatGPT can also be utilized to generate comprehension questions in relation to the generated text, facilitating a more comprehensive learning experience for students. In fact, it can even generate multiple types of questions just in case one type was not enough i.e. it can generate questions to target different aspects of the text such as vocabulary, comprehension and so on.
In addition to that, ChatGPT also allows for the effortless adaptation of that text, or any text for that matter, for use with a different CEFR proficiency level. By simply prompting it with different parameters or providing additional guidance to the AI, EFL teachers can efficiently repurpose the text to suit the needs of another class, thus maximizing the utility of the generated content. This flexibility in material adaptation offers incredible ease in streamlining the process of creating diverse resources [31].
4.6.2. Criteria for Assessing Writing Proficiency
Assessment has an increasingly significant influence on the education policies of various countries. It also affects language assessment in classroom settings. Language assessment plays a significant role in helping language teachers around the world to identify their students at their appropriate levels, diagnose their strengths and weaknesses and grade their performance during and at the end of a syllabus or course. It is considered the main influence of teaching and learning activities as teachers may plan interventions or activities that suited their students once their learning abilities had been identified. As mentioned earlier, teaching how to write well is a complex process. Consequently, writing assessment is also difficult to conduct.
Assessment of students’ writing skills is considered an issue when it comes to language testing. It is made even more essential because a good writing ability is highly demanded after by higher education institutions and employers. Teachers have been spending long hours to ensure the validity and reliability of their writing assessment practices. Assessment in writing can be conducted in many forms, depending on what the teacher desires. Teachers may instruct their students to write essays and complete project-based works or portfolios. Written tests have a few advantages that are difficult to be replicated. For example, the multiple-choice assessments are closed-ended questions that can effectively measure students’ answering abilities. Writing assessment is a process that assesses students’ writing performance within the class and can occur at many stages throughout the learning period and come in different forms. At various points within the assessment process, teachers usually play different roles, such as a motivator, collaborator, critic and evaluator, and provide various kinds of responses. One of the main purposes of writing assessment is to produce feedback on students’ writing performance, which is crucial in the development of their writing skills. A study revealed that online assessments allowed for more interaction as compared to traditional paper-based assessment. They found that scores amongst the students who are involved in interactive online assessments were significantly higher than those who were assessed in a conventional way. Additionally, students who had their assessments using gadgets were more comfortable with the material at hand and this allowed for stress-free feedback session between the teacher and students [32].
4.7. Data Analysis Techniques
To answer the first study question, classroom observations were conducted to investigate teacher-student interactions. Four observations were made in four different classrooms with the same teacher of English. As a result, in this study, classroom observations were conducted with tenth-grade students in four different classrooms totalling roughly 40 students and the teacher of English who taught the classroom. The study took place between February and March, 2021. The last part of this research was to answer the second research question. Interviews were conducted with six students from different classes who had been observed. The interview techniques was semi-structured interviews where the interview was conducted to obtain the research objectives through a question and answer face to face between the interviewer and the informant and verified the data gathered from the observation.
4.7.1. Qualitative Analysis of Student Responses and Feedback
In analyzing the data of this study, the researchers used four techniques and the data analysis is as follows: (1). transcribing data; the process of transcription starts after interviews have been conducted or events have been reported. Transcription requires direct examination of knowledge by careful listening (and/or watching) repeatedly, and this is a significant first step in data analysis. (2). Data Condensation; According to the process of choosing, focusing, clarifying, abstracting, and/or changing the data found in the complete text (body) of written-up, field notes, interview transcripts, records, and other analytical materials is referred to as data condensation (3). The data display deals with the provision of ordered, compressed, information the assembly which allows the drawing of a conclusion. (4). Drawing and verifying conclusions; conclusions should also be tested as the analyst moves along. At this point, to establish the conclusions regarding the analysis, the data analysed were read and reread. The results were then double-checked by going over the data as many times as feasible.
Table 5: ELT class
|
Interaction Type
|
Total
|
|
Initiation
|
|
|
Procedural Questions
|
7
|
|
Convergent Questions
|
17
|
|
Divergent Questions
|
15
|
|
Response
|
|
|
Student Response, Specific
|
25
|
|
Open-ended or student-initiated
|
13
|
|
Silence
|
1
|
|
Feedback
|
|
|
Acknowledging the correct answer
|
4
|
|
Indicating an incorrect answer
|
3
|
|
Praising
|
5
|
|
Expanding or modifying a student's answer
|
2
|
|
Summarizing
|
2
|
4.8. Ethical Considerations
4.8.1. Informed Consent Procedures for Participation:
Informed consent is crucial in any educational research or participation to ensure that individuals understand the nature of their involvement and the potential risks and benefits associated with it. In an ELT class, informed consent procedures should be implemented to ensure that students and, if applicable, their guardians are fully informed about the purpose of the activities, their rights as participants, and any potential risks involved. This may include providing clear and understandable explanations of the activities planned, allowing students to ask questions, and obtaining written consent before any participation begins. It's essential to ensure that participation is voluntary and that students have the option to withdraw at any time without repercussions.
4.8.2. Ensuring Privacy and Confidentiality of Student Data:
Protecting the privacy and confidentiality of student data is paramount in maintaining trust and ethical standards in education. Teachers and educational institutions must implement measures to safeguard student information from unauthorized access, use, or disclosure. This includes ensuring that student records are stored securely, restricting access to sensitive data only to authorized personnel, and obtaining consent before sharing any identifiable information with third parties. Additionally, when conducting research or assessments that involve collecting student data, it's essential to anonymize data wherever possible to prevent the identification of individual students. Regular reviews of data protection policies and procedures should be conducted to ensure compliance with relevant laws and regulations, such as the Family Educational Rights and Privacy Act (FERPA) in the United States.
4.9. Limitations and Challenges
4.9.1. Technical Issues with ChatGPT and Padlet Integration:
Integrating ChatGPT with Padlet for educational purposes may present technical challenges that could impact the effectiveness of the learning experience. Some potential technical issues may include compatibility issues between ChatGPT and Padlet platforms, such as formatting discrepancies or limitations in the types of interactions supported. Additionally, network connectivity issues or server downtimes could disrupt the seamless integration between the two platforms, affecting the flow of communication and collaboration in the classroom. It's essential to have a contingency plan in place to address these technical issues promptly, such as providing alternative communication channels or technical support resources for students and educators.
4.9.2. Potential Bias in Data Collection and Analysis:
When collecting and analyzing data in educational settings, there's a risk of potential bias that could skew the results and conclusions drawn from the study. Bias may arise from various sources, such as the selection of participants, the design of assessment tools, or the interpretation of data. In the context of using ChatGPT and Padlet, bias could manifest in the form of disproportionate participation from certain student groups, leading to unequal representation of perspectives or experiences. Similarly, biases in the design of prompts or questions posed to students could influence the types of responses elicited, affecting the validity and reliability of the data collected. To mitigate potential bias, it's important to employ diverse and inclusive sampling methods, use validated assessment instruments, and employ rigorous data analysis techniques, such as triangulation and peer review. Additionally, transparent reporting of methods and findings can help identify and address potential biases in the research process.