Linda Galligan

The integration of online learning games in mathematics education is a rapidly growing area, driven by ongoing technological progress and the recognized potential to improve student learning experiences. Effective technological support is essential for enhancing students’ understanding and engagement in mathematics. This study critically assesses the effectiveness of MangaHigh, an online game-based learning (GBL) resource featuring adaptive learning technology, in an Australian primary school setting. Using a mixed-methods case study approach, data were gathered through surveys completed by 72 year 6 students and a semi-structured interview with their classroom teacher. The results show that the teacher viewed MangaHigh as a tool that encourages student engagement and helps in understanding specific mathematical concepts, aligning with recent research indicating GBL can increase motivation and conceptual understanding. Survey data showed that most students believed MangaHigh assisted their understanding of mathematical concepts. Notably, gender-based differences in perceptions were observed, with more boys than girls perceiving MangaHigh as a helpful tool that makes learning mathematics enjoyable, boosts confidence, and simplifies concepts. However, statistical analysis revealed that these differences were not significant. These findings are placed within current research on digital skills and attitudes. Overall, the results suggest that mathematics teachers should think about incorporating technology into their teaching. The study also emphasizes the need for further research, as current studies on the impact of GBL tools like MangaHigh on primary school mathematics education are still limited.

Core mathematics courses are fundamental to the academic success of engineering students in higher education. These courses equip students with skills and knowledge applicable to their specialized fields. However, first-year engineering students often face significant challenges in mathematics due to a range of factors, including insufficient preparation, mathematics anxiety, and difficulty connecting theoretical concepts to real-life applications. The transition from secondary to tertiary mathematics remains a key area of educational research, with ongoing discussions about effective pedagogical approaches for teaching engineering mathematics. This study utilized a belief survey to gain general insights into the attitudes of first-year mathematics students towards the subject. In addition, it employed the activity theory framework to conduct a deeper exploration of the experiences of first-year engineering students, aiming to identify contradictions, or “tensions,” encountered within a flipped-classroom learning environment. Quantitative data were collected using surveys that assessed students’ self-reported confidence, competence, and knowledge development. Results from Friedman’s and Wilcoxon’s Signed-Rank Tests, conducted with a sample of 20 participants in 10 flipped-classroom sessions, statistically showed significant improvements in all three areas. All of Friedman’s test statistics were above 50, with p-values below 0.05, indicating meaningful progress. Similarly, Wilcoxon’s Signed-Rank Test results supported these findings, with p values under 0.05, leading to the rejection of the null hypothesis. The qualitative data, derived from student questionnaire comments and one-to-one interviews, elucidated critical aspects of flipped-classroom delivery. The analysis revealed emerging contradictions (“tensions”) that trigger “expansive learning”. These tensions encompassed the following: student expectation–curriculum structure; traditional versus novel delivery systems; self-regulation and accountability; group learning pace versus interactive learning; and the interplay between motivation and anxiety. These tensions are vital for academic staff and stakeholders to consider when designing and delivering a first-year mathematics course. Understanding these dynamics can lead to more effective, responsive teaching practices and support student success during this crucial transition phase.

This paper reports on research that extends knowledge about higher education students’ perceptions of online engagement. In particular, the study aimed to identify what students thought engagement was and how they experienced it. Understanding students’ views about online engagement will provide a more comprehensive understanding of the topic and should assist instructional designers to support academic staff to develop online courses that are more likely to engage their students. Using a mixed-methods approach, the study found that students felt most engaged with learning when doing practical, hands-on activities. Additional findings from the qualitative and quantitative data are highlighted, with some differences between the students’ perceptions in the different types of data, particularly concerning social engagement. This suggests that further research is warranted. The paper offers several practical implications for student learning.

This article reports on an exploratory case study that applied the Community of Inquiry framework in the K-12 Philippine setting, where there are limited studies on blended learning interactions and experiences. The study examined blended learning interactions across three schools in the Philippine K-12 system to investigate the following: (1) what is the nature of interactions in the blended learning classes? and (2) how do the interactions indicate learning communities as outcomes of blended learning? A mixed method approach to data collection was undertaken, which included student surveys, focus group discussions, teacher interviews, and class observations. The constant comparative analysis uncovered thick descriptions of blended learning interactions. Findings uncovered three themes on blended learning across levels of interactions within the Community of Inquiry presences: (i) best of both worlds, (ii) learning anytime and anywhere, and (iii) learning with technology. Descriptive statistics indicated high mean ratings across the presences, revealing positive experiences afforded by the use of various technologies and social media. The study concluded that learning communities are an outcome of blended learning interactions. A Developmental Model for K-12 Blended Learning Communities was recommended to inform teacher professional development on pedagogies and practices supportive of learning community building in contexts where blended learning may continue to thrive.

Sentiment analysis AKA opinion mining is one of the most widely used NLP applications to identify human intentions from their reviews. In the education sector, opinion mining is used to listen to student opinions and enhance their learning-teaching practices pedagogically. With advancements in sentiment annotation techniques and AI methodologies, student comments can be labelled with their sentiment orientation without much human intervention. In this review article, (1) we consider the role of emotional analysis in education from four levels: document level, sentence level, entity level, and aspect level, (2) sentiment annotation techniques including lexicon-based and corpus-based approaches for unsupervised annotations are explored, (3) the role of AI in sentiment analysis with methodologies like machine learning, deep learning, and transformers are discussed, (4) the impact of sentiment analysis on educational procedures to enhance pedagogy, decision-making, and evaluation are presented. Educational institutions have been widely invested to build sentiment analysis tools and process their student feedback to draw their opinions and insights. Applications built on sentiment analysis of student feedback are reviewed in this study. Challenges in sentiment analysis like multi-polarity, polysemous, negation words, and opinion spam detection are explored and their trends in the research space are discussed. The future directions of sentiment analysis in education are discussed.

Driven by the increased availability of Learning Management System data, this study explored its value and sought understanding of student behaviour through the information contained in activity level log data. Specifically, this study examined analytics data to understand students’ engagement with online videos. Learning analytics data from the MoodleTM and Vimeo® platforms were compared. The research also examined the impact of video length on engagement, and how engagement with videos changed over the course of a semester when multiple video resources were used in a course. The comparison in platform learning analytics showed differences in metrics thus offering a caution to users relying on unidimensional metrics. While the results support the notion that log data do provide educators with an opportunity for review, the time and expertise in extracting, handling, and using the data may stifle its widespread adoption.

Artificial Intelligence (AI) is a fast-growing area of study that stretching its presence to many business and research domains. Machine learning, deep learning, and natural language processing (NLP) are subsets of AI to tackle different areas of data processing and modelling. This review article presents an overview of AI’s impact on education outlining with current opportunities. In the education domain, student feedback data is crucial to uncover the merits and demerits of existing services provided to students. AI can assist in identifying the areas of improvement in educational infrastructure, learning management systems, teaching practices and study environment. NLP techniques play a vital role in analyzing student feedback in textual format. This research focuses on existing NLP methodologies and applications that could be adapted to educational domain applications like sentiment annotations, entity annotations, text summarization, and topic modelling. Trends and challenges in adopting NLP in education were reviewed and explored. Context-based challenges in NLP like sarcasm, domain-specific language, ambiguity, and aspect-based sentiment analysis are explained with existing methodologies to overcome them. Research community approaches to extract the semantic meaning of emoticons and special characters in feedback which conveys user opinion and challenges in adopting NLP in education are explored.

Secondary mathematics teachers working in the Australian education sector are required to plan lessons that engage with students of different genders, cultures and levels of literacy and numeracy. Teaching Secondary Mathematics engages directly with the Australian Curriculum: Mathematics and the Australian Professional Standards for Teachers to help preservice teachers develop lesson plans that resonate with students. This edition has been thoroughly revised and features a new chapter on supporting Aboriginal and Torres Strait Islander students by incorporating Aboriginal and Torres Strait Islander cultures and ways of knowing into lessons. Chapter content is supported by new features including short-answer questions, opportunities for reflection and in-class activities. Further resources, additional activities, and audio and visual recordings of mathematical problems are also available for students on the book's companion website. Teaching Secondary Mathematics is the essential guide for preservice mathematics teachers who want to understand the complex and ever-changing Australian education landscape.