Online Writing Instruction in Indonesia: Causes of anxiety problems and strategies of solutions
Abstract:Online learning brings EFL students the new experience of writing instruction. On the one hand, the new experience in online learning may lead to excitement; on the other hand, it may also result in problems such as anxiety. The current study aims at tracing the students' writing anxiety levels, identified the causes of anxiety problems, and put forward strategies of solutions. The results of the data analyses show that out of 149 students involved in this study, 115 students had a high level of writing anxiet… Show more
“…Quality issues with written English in global and Indian contexts Quality issues with written English have been a subject of academic research. Students worldwide, especially in non-English countries, experience anxiety in writing English texts (Kurniasih et al, 2023;Quvanch and Si Na, 2022). Teachers, adding to this anxiety about writing in L2, have issues with training (Toquero et al, 2021), different orientations (Pham and Truong, 2021) and technological autonomy in classrooms by instructors (Sheerah and Yadav, 2022).…”
Purpose
This study aims to examine the effectiveness of the Central Board of Secondary Education (CBSE)-based English textbooks and question papers in developing second-language higher-order thinking skills (HOTS).
Design/methodology/approach
Descriptive analysis establishes a causal relationship between learning objectives and second language (L2) writing proficiency. Content analysis is used to compare and analyze tabulated data for textbooks and question papers for the English language by the National Council of Educational Research and Training (NCERT) and CBSE. This method categorizes the materials and their assessments under HOTS and lower-order thinking skills to ascertain the relationship between learning objectives and L2 writing proficiency.
Findings
The study highlights teaching material and assessment shortcomings and their alignment with learning outcomes to enhance students' writing skills. It underscores the need for HOTS-focused materials, discussing their impact on writing skills. The study also explores how textbook–question paper mismatch hampers Bloom's taxonomy-based cognitive skills.
Practical implications
This research illuminates the efficacy of teaching and learning English as a second language (ESL) writing skills to improve the quality of education, which has real-world implications. The study highlights flaws in the educational system in India and suggests curricular and pedagogical changes.
Originality/value
The research examines NCERT and CBSE ESL textbooks and question papers to align teaching and assessment methods. The results aim to improve education through ESL writers' HOTS.
“…Quality issues with written English in global and Indian contexts Quality issues with written English have been a subject of academic research. Students worldwide, especially in non-English countries, experience anxiety in writing English texts (Kurniasih et al, 2023;Quvanch and Si Na, 2022). Teachers, adding to this anxiety about writing in L2, have issues with training (Toquero et al, 2021), different orientations (Pham and Truong, 2021) and technological autonomy in classrooms by instructors (Sheerah and Yadav, 2022).…”
Purpose
This study aims to examine the effectiveness of the Central Board of Secondary Education (CBSE)-based English textbooks and question papers in developing second-language higher-order thinking skills (HOTS).
Design/methodology/approach
Descriptive analysis establishes a causal relationship between learning objectives and second language (L2) writing proficiency. Content analysis is used to compare and analyze tabulated data for textbooks and question papers for the English language by the National Council of Educational Research and Training (NCERT) and CBSE. This method categorizes the materials and their assessments under HOTS and lower-order thinking skills to ascertain the relationship between learning objectives and L2 writing proficiency.
Findings
The study highlights teaching material and assessment shortcomings and their alignment with learning outcomes to enhance students' writing skills. It underscores the need for HOTS-focused materials, discussing their impact on writing skills. The study also explores how textbook–question paper mismatch hampers Bloom's taxonomy-based cognitive skills.
Practical implications
This research illuminates the efficacy of teaching and learning English as a second language (ESL) writing skills to improve the quality of education, which has real-world implications. The study highlights flaws in the educational system in India and suggests curricular and pedagogical changes.
Originality/value
The research examines NCERT and CBSE ESL textbooks and question papers to align teaching and assessment methods. The results aim to improve education through ESL writers' HOTS.
A significant component of the online learning platform is the online exercise assessment system, which has access to a wealth of past student exercise data that may be used for data mining research. However, the data from the present online exercise system is not efficiently used, making each exercise less relevant for students and decreasing their interest and interaction with the teacher as she explains the activities. In light of this, this research creates an exercise knowledge map based on the connections between workouts, knowledge points, and previous tournaments. The neural matrix was then improved using cross-feature sharing and feature augmentation units to deconstruct the workout recommendation model. The study also developed an interactive text sentiment analysis model based on the expansion of the self-associative word association network to assess how students interacted after the introduction of the personalized exercise advice teaching approach. The outcomes demonstrated that the suggested model’s mean diversity value at completion was 0.93, an increase of 0.14 and 0.23 over collaborative filtering algorithm and DeepFM (deep factor decompose modle), respectively, and that the proposed model’s final convergence value was 92.3%, an improvement of 2.3 and 4.1% over the latter two models. The extended model used in the study outperformed the support vector machine (SVM) and Random Forest models in terms of accuracy by 5.9 and 1.7%, respectively. In terms of F1 value indicator, the model proposed by the research has a value of 90.4%, which is 2.5 and 2.1% higher than the SVM model and Random Forest model; in terms of recall rate indicators, the model proposed by the research institute has a value of 94.3%, which is an increase of 6.2 and 9.8% compared to the latter two models. This suggests that the study’s methodology has some application potential and is advantageous in terms of customized recommendation and interactive sentiment recognition.
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