The impact of artificial intelligence on learner–instructor interaction in online learning

Artificial intelligence (AI) systems offer effective support for online learning and teaching, including personalizing learning for students, automating instructors’ routine tasks, and powering adaptive assessments. However, while the opportunities for AI are promising, the impact of AI systems on the culture of, norms in, and expectations about interactions between students and instructors are still elusive. In online learning, learner–instructor interaction (inter alia, communication, support, and presence) has a profound impact on students’ satisfaction and learning outcomes. Thus, identifying how students and instructors perceive the impact of AI systems on their interaction is important to identify any gaps, challenges, or barriers preventing AI systems from achieving their intended potential and risking the safety of these interactions. To address this need for forward-looking decisions, we used Speed Dating with storyboards to analyze the authentic voices of 12 students and 11 instructors on diverse use cases of possible AI systems in online learning. Findings show that participants envision adopting AI systems in online learning can enable personalized learner–instructor interaction at scale but at the risk of violating social boundaries. Although AI systems have been positively recognized for improving the quantity and quality of communication, for providing just-in-time, personalized support for large-scale settings, and for improving the feeling of connection, there were concerns about responsibility, agency, and surveillance issues. These findings have implications for the design of AI systems to ensure explainability, human-in-the-loop, and careful data collection and presentation. Overall, contributions of this study include the design of AI system storyboards which are technically feasible and positively support learner–instructor interaction, capturing students’ and instructors’ concerns of AI systems through Speed Dating, and suggesting practical implications for maximizing the positive impact of AI systems while minimizing the negative ones.

PENGARUH INTERACTION ENVIRONMENT DAN LEARNER CHARACTERISTIC TERHADAP KEPUASAN DALAM PENGGUNAAN SISTEM E-LEARNING

Studi ini bertujuan untuk mengetahui ada tidaknya pengaruh yang signifikan antara interaction-environment dan learner-characteristic sebagai variabel independen terhadap e-learning satisfaction sebagai variabel dependen. Disini faktor interaction- environment direpresentasikan melalui variabel-variabel Learner-content interaction, Learner- instructor interaction, dan Learner-learner interaction. Sedangkan faktor learner- characteristics direpresentasikan melalui variabel-variabel Self-efficacy dan Self- directed. Studi dilakukan pada sebuah perguruan tinggi swasta di Jakarta, dan sebagai sampel penelitian dipilih para mahasiswa di institusi tersebut dengan teknik purposive sampling. Metode analisis data menggunakan teknik regresi linier berganda. Hasil olah data menunjukkan bahwa semua variabel independen berpengaruh positif dan signifikan terhadap variabel dependen, kecuali Learner-learner interaction tidak berpengaruh signifikan terhadap E-learning satisfaction.

The Impact of Integrated Mobile System on Students' Academic Achievement, Interaction and Satisfaction

This study explored the effectiveness of Blended Learning, hereafter (BL) on students’ academic achievement, interaction and satisfaction in higher education. The Integrated M-Learning and ELearning system, (IMELS) was utilized on a sample of students (n = 52) who attended Artificial Intelligent course at a large urban college in Jordan. The pretest/ post-test design was used to investigate the students’ academic achievement, interaction and satisfaction. ANOVA test was conducted to compare the achievement scores between the BL with IMELS group and face-to-face learning group. The post-test revealed a significant difference between the two groups in favour of the treatment group. Findings also showed that interaction types were positively associated with satisfaction of the students exposed to the IMELS in favour of learner-instructor interaction. This study has contributed to a better understanding of new technologies like IMELS in BL environment, which can affect positively the students' academic achievement, interactions and their satisfaction.

Factors Affecting Learners’ Academic Success in Online Liberal Arts Courses Offered by a Traditional Korean University

This study aimed to empirically examine the factors affecting full-time undergraduate students’ satisfaction and academic performance measured by grades using an existing large administrative dataset. The sample consisted of 21,662 undergraduate students who took online liberal arts courses offered by a large traditional Korean university in the spring semester of 2020. The theoretical framework of this study was formulated by selectively adopting and slightly modifying some of the factors from Choi’s conceptual model for adult dropout from online degree programs. The findings indicated that gender, previous GPA, campus, type of online course, the relevance of the course, adequacy of assignments and assessments, learner-instructor interaction, and learner-content interaction significantly affect students’ degree of satisfaction with online liberal arts courses. This study also found that students who considered the course less relevant to their goals or interests, had a low previous GPA, had frequent learner-instructor interactions, few learner-content interactions, and a low level of course satisfaction are more likely to earn a grade of B, C, or lower than to receive an A in online liberal arts courses.

FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUASAN BELAJAR JARAK JAUH MAHASISWA VOKASI DI MASA PANDEMI COVID-19

Pada awal tahun 2020 hampir semua negara di dunia mengalami masa pandemi COVID-19 termasuk negara kita Indonesia sehingga pembelajaran dilakukan secara secara jarak jauh dari rumah mahasiswa masing-masing. Pembelajaran jarak jauh secara daring juga dialami pada program vokasi di Fakultas Teknik, Universitas Negeri Surabaya. Kepuasan belajar mahasiswa secara jarak jauh di evaluasi untuk perbaikan program selanjutnya. Tujuan penelitian dalam era COVID ini adalah untuk menguji faktor-faktor yang diprediksi dapat mempengaruhi kepuasan belajar jarak jauh secara daring mahasiswa vokasi di masa pandemi COVID-19. Kami melakukan penelitian survei untuk mengumpulkan data melalui kuesioner yang telah disusun dalam google form dan disebar melalui WAG. Pengambilan sample dilakukan secara convenience sampling pada mahasiswa program vokasi di Fakultas Teknik, Universitas Negeri Surabaya. Pada bulan Juli sampai Agustus 2020 dilakukan pengambilan data secara online, dan diperoleh 170 responden. Dalam penelitian ini data diananalisis secara kuantitatif menggunakan program SPSS. Dari sembilan faktor yang diprediksi berpengaruh terhadap kepuasan belajar jarak jauh, hanya empat faktor terbukti secara signifikan berpengaruh terhadap kepuasan belajar jarak jauh yaitu sumber belajar elektronik yang baik (good e-resourches), konten pembelajaran (learning content), manfaaat yang dirasakan (perceived usefulness) dan interaksi antara pembelajar dan dosen (learner-instructor interaction). Penelitian ini memberikan kontribusi terhadap baik terhadap pengelola pembelajaran maupun dosen.

THE IMPACT OF CLASSROOM RESPONSE SYSTEM ON PEER EVALUATION

Peer evaluation being an active type of learning develops learners’ interactivity, speaking, listening, critical thinking abilities. Unlike the passive learning, in active learning students are more engaged in the evaluation process of presentation made by their peers, which significantly encourages student participation. Applying Classroom Response System students gain the ability to instantly respond and react, since this activity requires continuous attention. Promoting student-instructor interaction this technique leads to the involvement of students to class discussion simultaneously providing information about efficacy of the comprehension of the new topic. A significant point to be taken into consideration is the individual approach to every student.

Trifecta of Student Engagement

This chapter describes a framework adapted from Michael Moore's three essential areas: student-content interaction, student-student interaction, and student-instructor interaction for engaging students in online courses. To be fully engaged in an online course, students need to be engaged with the course curriculum content, with their peers, and with their instructor. When students are engaged in all three areas, it is referred to as the Trifecta of Student Engagement. This chapter incorporates literature on each area of the Trifecta of Student Engagement: student-to-content engagement, student-to-student engagement, and student-to-instructor engagement as well as some suggested synchronous and asynchronous digital tools.

Engaging Students in Emergency Remote Teaching

The COVID-19 pandemic has resulted in emergency remote teaching taking place globally. Despite the abrupt and rapid transition as well as the temporary nature of emergency remote teaching, it is possible to implement quality online teaching. Instructors can benefit from a review of findings and strategies found in online learning literature. This chapter discusses the challenges of emergency remote teaching and recommends suitable teaching strategies that can be quickly implemented by instructors. The focus is on strategies that can help to engage students by promoting learner-content interaction, learner-instructor interaction, and learner-learner interaction. This chapter also discusses strategies that can build a community of inquiry during emergency remote teaching. Future research directions are proposed.

Predictors of students’ perceived learning in off-campus learning environment: Online interactions are not enough

This study aimed to investigate how three online interaction variables (i.e., learner-instructor interaction, learner-content interaction, and learner-learner interaction) and self-efficacy for learning can predict students’ perceived learning in an off-campus learning environment. A total of 654 polytechnic students participated in the study. By controlling gender and age, regression results showed that self-efficacy for learning was the significantly strongest predictor of perceived learning, followed by learner-content interaction. Perceived learning and learner-instructor interaction for males were significantly higher than females. Finally, implications of these findings along with limitations of the study and directions for future research are discussed in the paper.