How Can Digital Technology Enhance Mathematics Teaching and Learning?

As digital technology becomes more ubiquitous in society and education, mathematics teachers are expected to design and integrate technology-enriched learning environments effectively. This task encompasses many challenges, but primarily, it entails the identification of how technology may produce insights. This study examines several categories of core mathematical processes that can be enhanced by the integration of dynamic interactive software such as identifying properties, connecting multiple representations, and solving problems, among others. The process of visualization appears at the center of dynamic and interactive mathematics learning environments. Evidence of its functionality and the benefits it reports to the teaching and learning process for each category is presented. Further discussion on the challenges that mathematics teacher education programs and teachers face—not only in their digital competences but also in the role they play—are outlined.

Influence of Multimedia and Cognitive Strategies in Deep and Surface Verbal Processing

The traditional view of linguistic-verbal intelligences focuses on individual linguistic abilities at the levels of phonology, syntax, and semantics. This chapter discusses the individual linguistic abilities from a text-comprehension perspective. The chapter examines the roles of multimedia and cognitive prompts in deep and surface verbal processing. Drawn from research in working memory, multimedia learning, and deep processing, a theoretical framework is proposed to promote learners' deep and surface learning in reading. Evidence from empirical studies are reviewed to support the underlying theoretical assumptions of the framework. The theoretical and practical significance of the theoretical framework is discussed with suggestions for future research.

Understanding the Role of Digital Technology in Multiple Intelligence Education

The theory of multiple intelligences has been embraced by the education and research communities worldwide. Substantial research has been conducted to understand multiple intelligences and learning. However, studies that examine how various types of technology affect across the board the different types of intelligences in learning is lacking. This chapter reviews the multiple intelligence (MI) theory and how emergent technologies can be used to support MI learning in education using a meta-analysis method. The results reveal that bodily-kinesthetic is most responsive to technology-based intervention compared to other types of intelligences and that immersive and visual images are effective in improving verbal linguistic and bodily-kinesthetic intelligences. Discussion of the findings are made along with their implications in educational practices. Suggestions for future research and practice are made in regard to multiple intelligence and emergent digital technology.

Multiple Intelligences and Digital Learning Game Design

Empirical research that draws a framework on how the theory of MI could be incorporated in (learning) games is non-existent. Furthermore, the theory of MI fits well into the concept of individualization, as it distinguishes between individuals in terms of their abilities. In light of this, the chapter reports on the first evidence-based set of mappings between this theory and fundamental constructs of games known as mechanics. These mappings can be utilized by designers in the individualization paradigm of player-centered game design as guidelines on what mechanics to include in their design when targeting an audience with specific MI profiles. Such individualization can potentially positively affect the game experience of players while establishing the proper frame for affecting learning. As such, these mappings, available in form of a recommendation tool, act as guidelines on how to design (learning) games while considering the intelligences of the target audience.

Game Development-Based Learning

This chapter presents the findings from a quasi-experimental study analyzing the effect of Game Development-Based Learning on students' academic performance in programming courses in Jordan. The study tested an argument proposing a positive significant association between GDBL instruction and students' performance. The analysis of variance results investigating the effect of enrollment and completion of a concurrent GDBL course to normal courses found that the treatment group outperformed two other groups: the control and the comparison group. The positive gains in the post-assessment scores, were consistent across the two programming courses: C++ and Object-Oriented Programming. This finding confirms the earlier results across countries and contexts documenting the salubrious effect of GDBL on students' academic performance in Computer Science and Information Technology courses. Findings also support the overarching constructionist approach where the use of scaffolding and technology in instruction and assessment yield better academic outcomes for learners.

Geolocation for the Improvement of Spatial and Naturalist Intelligence in Primary Education

Geolocation provides a new learning model by combining physical and digital content, creating an enriched and interactive universe. This mobile technology offers new opportunities for the promotion of learning inside and outside the classroom, linked to multiple intelligences, in particular, to the spatial and naturalistic intelligences. Taking these premises into account, an analysis of several geolocation applications (N=20) is carried out in order to determine their potential to develop spatial and naturalistic intelligences. To this end, case study methodology is adopted, and an analysis instrument is proposed consisting of 15 indicators grouped into three dimensions: 1) geolocation, 2) spatial intelligence (spatial orientation and spatial representation), and 3) naturalistic intelligence (physical geography and environment). Although the geolocation applications analyzed boost spatial intelligence through the different options they incorporate, the same cannot be said of the naturalist one. It is considered relevant that they include contents oriented to environmental awareness.

An Educational Data Mining Application by Using Multiple Intelligences

The aim of this chapter is to illustrate both uses of data mining methods and the way of these methods can be applied in education by using students' multiple intelligences. Data mining is a data analysis methodology that has been successfully used in different areas including the educational domain. In this context, in this study, an application of EDM will be illustrated by using multiple intelligence and some other variables (e.g., learning styles and personality types). The decision tree model was implemented using students' learning styles, multiple intelligences, and personality types to identify gifted students. The sample size was 735 middle school students. The constructed decision tree model with 70% validity revealed that examination of mathematically gifted students using data mining techniques may be possible if specific characteristics are included.

Creating Geospatial Thinkers

In today's contemporary digital world, where geospatial technologies are an integral part of society, it is imperative that students learn to think spatially. The ability to think spatially is crucial for making well-informed decisions, and these skills are rapidly becoming exponentially more important. This chapter will explore the complexity of spatial thinking, and multiple spatial thinking skills will be identified. Methods best suited for delivering content that fosters the improvement of these spatial thinking skills will also be discussed. The chapter concludes with an exploration of some of the necessary elements required for the sustained use of geospatial technologies in the classroom and offers recommendations for transformation in teacher practice such as pre-service intervention, continuous follow-up and coaching, and curriculum modifications, which include the direct instruction of both spatial thinking and geospatial technologies.

Enhancing 21st Century Learning Using Digital Learning Objects and Multiple Intelligence Theory

The educational system is undergoing radical pressure to change. The increased need for individuals to learn and adapt has resulted in a huge demand for higher education. However, higher educational institutes are failing to keep pace with learner and societal needs. Firstly, the skills profile required for individuals to succeed is changing; there is a change in emphasis from discipline-specific to transversal skills due to the dynamic labor market. Secondly, the learner profile has changed with individuals from diverse backgrounds, cultures, abilities, and contexts, and catering for such a diverse range of students is challenging. Technology is a key enabler in providing HEIs with the means to address such issues. This chapter explores a conceptual model which integrates pedagogical approaches such as multiple intelligence theory, learning styles, competency-based education with digital technologies to offer a solution to some of the concerns facing higher education in the 21st century.

A Framework for Human-Technology Social Systems

Advancements in semi- and fully-autonomous systems have made human-technology interaction a dynamic and social process. In this chapter, the authors highlight the importance of interpersonal interactions between human and technology and how they can be modeled, tracked, and fostered in the context of adaptive instructional systems. They will first introduce a human-technology social systems framework, which integrates individual factors (human and technology), situational factors (e.g., stress), and team interaction-relevant factors (e.g., communication and team cognition) that contribute to various team-related outcomes (e.g., learning and performance). Using examples from interactive virtual agents and educational technology, they discuss attributes of technology that should be considered to optimize joint learning and performance in applied contexts. The proposed framework points to novel research directions and is likely to offer an understanding of mechanisms that could enhance learning opportunities in diverse socioemotional contexts.