Engaging and Authentic Education Practices

This chapter is an argument for and celebration of lessons learned during the pandemic of 2020 toward the end of designing authentic and engaging learning experiences across education systems. In the forced shift to online and multimodal learning, educators and students experienced challenges of access, equity, and low engagement. However, there is an opportunity to extrapolate the lessons of 2020 for the betterment of education into the future. This chapter describes lessons pertaining to planning and collaboration, classroom environment, humanized online practices, as well as empowering pedagogy. The chapter concludes with three practical application examples for further thought and inspiration. The pandemic year can be one to survive and never think about again or, with the proper perspective, education's greatest learning moment.

Critical Care Nurses’ Perceptions of Clinical Alarm Management on Nursing Practice

The management of alarms is a key responsibility of critical care nurses. A qualitative study with focus group interviews were conducted with 37 nurses in Taiwan. Four main themes were derived: the foundation of critical care practice, a trajectory of adjust alarms management, negative impacts on care quality and patient safety, hope for remote control and multimodal learning. Results revealed that diverse training methods may facilitate nursing competency and devices usability to promote critical care.

The challenges of dynamic teacher training for a short English for academic purposes course when using multimodal digital platforms: a case study

Despite the benefits of multimodal technology in the language classroom and common practice to introduce digital tools in language teaching, research has shown that many language teachers do not feel confident to engage with and create online multimodal learning resources and environments. This exploratory study examines data from five experienced English for Academic Purposes (EAP) teachers and discusses the dynamic challenges faced when training them to engage with multimodal teaching, learning, and assessment methods, such as digital learning, confidence and community building, and supporting them in creating multimodal learning resources. It also discusses the Dynamic Teacher Training model developed as a result of this experience to support teachers in developing the skills they needed to fully engage with the different digital teaching tools and teacher feedback on this.

Does ‘WOW’ translate to an ‘A’? Exploring the effects of virtual reality assisted multimodal text on Chinese Grade 8 EFL learners’ reading comprehension

Purpose In recent years, the incorporation of multimedia into linguistic input has opened a new horizon in the field of second language acquisition (SLA). In the reading aspect, the advent of virtual reality (VR) technology extends the landscape of reading repertoire by engaging learners with auditory, visual and tactile multimodal input. This study aimed to examine the pedagogical potential of VR technology in enhancing learners’ reading comprehension. Methods Three classes including 131 Chinese 8th grade EFL students participated in this study. This study adopted mixed methods methodology and triangulated pre-post-retention tests, questionnaires, learning journals and interview data to compare three modes of text input on learners’ reading performance and cognitive processing. Results The results indicated that VR-assisted multimodal input significantly improved learners’ macrostructural comprehension in the short term, whereas there was no significant difference in retention performance. The findings revealed that reading multimodal text did not exceed learners’ memory capacity or impose extraneous cognitive load. Participants mainly reported favorably on the efficacy of multimodal input in assisting their reading. Conclusion This study was the first attempt to integrate VR technology with input presentation and cognitive processing and offered a new line of theorization of VR-assisted multimodal learning in the cognitive field of SLA.

Assessing the relationship between student learning characteristics and academic performance in chemical pathology in an undergraduate medical curriculum

Background: Teaching and learning chemical pathology requires that medical trainees interpret biochemical test results correctly (against the background of clinical information) to solve clinical problems, while being aware of factors that could affect results. To meet these competencies, students must possess certain learning characteristics. This study explored the relationship between student learning characteristics and academic performance in chemical pathology. It is expected that a better understanding of the relationship between students' learning characteristics and academic performance will help formulate strategies to enhance teaching and learning of this subject. Methods: This study was designed as an exploratory survey. Self-administered, validated questionnaires were used to obtain data on learning mode, learning style and learning approach from 250 fourth-year undergraduate medical students at a medical university in South Africa. One-way ANOVA and Pearson correlations were used to analyse the relationship between each learning characteristic and academic performance. Spearman’s rho was used to study the relationships between the three learning characteristics. Results: A response rate of 72% was obtained. The largest number of participants (35%; n = 63) were visual learners, pragmatists (25%; n = 45) and learned using a superficial approach (44%; n = 79). Multimodal learning mode, balanced learning style and deep learning approach were found to correlate significantly with better academic performance in chemical pathology (r = 0.262, 0.307 and 0.467, respectively; p ≤ 0.0001).Conclusions: Our findings reveal that multimodal learners with a balanced learning style who have a deep approach to learning performed well in chemical pathology. This concurs with findings by studies that report a positive association between these learning characteristics and academic performance in other subjects in medicine. We propose that to achieve effective student learning, chemical pathology educators explore alternative teaching and learning activities to move students towards these positive learning characteristics.

A New Era in Multimodal Learning Analytics: Twelve Core Commitments to Ground and Grow MMLA

Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the learning analytics community. The Society of Learning Analytics Research is home to the CrossMMLA Special Interest Group and regularly hosts workshops on MMLA during the Learning Analytics Summer Institute (LASI). In this paper, we articulate a set of 12 commitments that we believe are critical for creating effective MMLA innovations. Moreover, as MMLA grows in use, it is important to articulate a set of core commitments that can help guide both MMLA researchers and the broader learning analytics community. The commitments that we describe are deeply rooted in the origins of MMLA and also reflect the ways that MMLA has evolved over the past 10 years. We organize the 12 commitments in terms of (i) data collection, (ii) analysis and inference, and (iii) feedback and data dissemination and argue why these commitments are important for conducting ethical, high-quality MMLA research. Furthermore, in using the language of commitments, we emphasize opportunities for MMLA research to align with established qualitative research methodologies and important concerns from critical studies.

On Task-specific Autonomy in Robotic Interventions: A Multimodal Learning-based Approach for Multi-level Skill Assessment during Cyborg Catheterization

Lack of learning-based methods for characterizing the multimodal data generated during cyborg catheterization hinders the drive towards autonomous robotic control. Also, multiplexing salient features from multiple data-sources can enhance effective assessment and classification of domain skills for apt intelligent surgeon-robot (cyborg) catheterization during intravascular interventions. In this study, task-specific autonomous intervention is envisioned upon an isomorphic master-slave robotic catheter system that exhibit hand defter techniques used in Cath Labs. To drive cyborg catheterization, stacking-based deep neural network is developed for three-level skill assessment.<br>

On Task-specific Autonomy in Robotic Interventions: A Multimodal Learning-based Approach for Multi-level Skill Assessment during Cyborg Catheterization

Lack of learning-based methods for characterizing the multimodal data generated during cyborg catheterization hinders the drive towards autonomous robotic control. Also, multiplexing salient features from multiple data-sources can enhance effective assessment and classification of domain skills for apt intelligent surgeon-robot (cyborg) catheterization during intravascular interventions. In this study, task-specific autonomous intervention is envisioned upon an isomorphic master-slave robotic catheter system that exhibit hand defter techniques used in Cath Labs. To drive cyborg catheterization, stacking-based deep neural network is developed for three-level skill assessment.<br>