Design of teacher assistance tools in an exploratory learning environment for algebraic generalisation

The MiGen project is designing and developing an intelligent exploratory environment to support 11-14 year-old students in their learning of algebraic generalisation. Deployed within the classroom, the system also provides tools to assist teachers in monitoring students' activities and progress. This paper describes the architectural design of these Teacher Assistance tools and gives a detailed description of one such tool, focussing in particular on the research challenges faced, and the technologies and approaches chosen to implement the necessary functionalities given the context of the project

Design and evaluation of teacher assistance tools for exploratory learning environments

We present our approach to designing and evaluating tools that can assist teachers in classroom settings where students are using Exploratory Learning Environments (ELEs), using as our case study the MiGen system, which targets 11-14 year old students' learning of algebra. We discuss the challenging role of teachers in exploratory learning settings and motivate the need for visualisation and notification tools that can assist teachers in focusing their attention across the whole class and inform their interventions. We present the design and evaluation approach followed during the development of MiGen's Teacher Assistance tools, drawing parallels with the recently proposed LATUX workflow but also discussing how we go beyond this to include a large number of teacher participants in our evaluation activities, so as to gain the benefit of different view points. We discuss the results of the evaluations, which show that participants appreciated the capabilities of the tools and were mostly able to use them quickly and accurately

Artificial Intelligence And Big Data Technologies To Close The Achievement Gap.

We observe achievement gaps even in rich western countries, such as the UK, which in principle have the resources as well as the social and technical infrastructure to provide a better deal for all learners. The reasons for such gaps are complex and include the social and material poverty of some learners with their resulting other deficits, as well as failure by government to allocate sufficient resources to remedy the situation. On the supply side of the equation, a single teacher or university lecturer, even helped by a classroom assistant or tutorial assistant, cannot give each learner the kind of one-to-one attention that would really help to boost both their motivation and their attainment in ways that might mitigate the achievement gap. In this chapter Benedict du Boulay, Alexandra Poulovassilis, Wayne Holmes, and Manolis Mavrikis argue that we now have the technologies to assist both educators and learners, most commonly in science, technology, engineering and mathematics subjects (STEM), at least some of the time. We present case studies from the fields of Artificial Intelligence in Education (AIED) and Big Data. We look at how they can be used to provide personalised support for students and demonstrate that they are not designed to replace the teacher. In addition, we also describe tools for teachers to increase their awareness and, ultimately, free up time for them to provide nuanced, individualised support even in large cohorts

Similarity-based grouping to support teachers on collaborative activities in exploratory learning environments

This paper describes a computer-based tool that helps teachers group their students for collaborative activities in the classroom, the challenge being to organise groups of students based on their recent work so that their collaboration results in meaningful interactions. Students first work on an exploratory task individually, and then the computer suggests possible groupings of students to the teacher. The complexity of the tasks is such that teachers would require too long a time to create meaningful groups. The paper describes the design of the tool, the algorithms and metrics used for generating the groups, the evaluation of the tool, and the pedagogical context in which the tool was designed

Scalable monitoring of student interaction indicators in exploratory learning environments

We present and evaluate a web-based architecture for monitoring student-system interaction indicators in Exploratory Learning Environments (ELEs), using as our case study a microworld for secondary school algebra. We discuss the challenging role of teachers in exploratory learning settings and motivate the need for visualisation and notification tools that can assist teachers in focusing their attention across the class and inform teachers' interventions. We present an architecture that can support such Teacher Assistance tools and demonstrate its scalability to allow concurrent usage by thousands of users (students and teachers)

An exploratory study on mathematics teacher educators’ beliefs and understandings about computational thinking

This paper reports an investigation of mathematics teacher educators’ views and perceptions on computational thinking (CT) and its impact on mathematical learning. We conducted semi-structured interviews with experienced mathematics teacher educators, all of whom have extensive experience with the use of digital technologies for mathematical teaching and learning and report on data from two of them. Our aim is to offer insights into how CT is perceived and understood by them, to support them in self-assessing their possession of CT practices, and how to support mathematics teachers and students in gaining CT. We offer ideas regarding the promotion of CT and its integration in mathematics teaching and learning

Design and evaluation of a case-based system for modelling exploratory learning behaviour of math generalisation

Exploratory learning environments (ELEs) promote a view of learning that encourages students to construct and/or explore models and observe the effects of modifying their parameters. The freedom given to learners in this exploration context leads to a variety of learner approaches for constructing models and makes modelling of learner behaviour a challenging task. To address this issue, we propose a learner modelling mechanism for monitoring learners’ actions when constructing/exploring models by modelling sequences of actions reflecting different strategies in solving a task. This is based on a modified version of case-based reasoning for problems with multiple solutions. In our formulation, approaches to explore the task are represented as sequences of simple cases linked by temporal and dependency relations, which are mapped to the learners’ behaviour in the system by means of appropriate similarity metrics. This paper presents the development and validation of the modelling mechanism. The model was validated in the context of an ELE for mathematical generalisation using data from classroom sessions and pedagogically-driven learning scenarios

Intelligent analysis and data visualisation for teacher assistance tools: the case of exploratory learning

While it is commonly accepted that Learning Analytics tools can support teachers’ awareness and classroom orchestration, not all forms of pedagogy are congruent to the types of data generated by digital technologies or the algorithms used to analyse them. One such pedagogy that has been so far underserved by Learning Analytics is exploratory learning, exemplified by tools such as simulators, virtual labs, microworlds and some interactive educational games. This paper argues that the combination of intelligent analysis of interaction data from such an exploratory learning environment (ELE) and the targeted design of visualisations has the benefit of supporting classroom orchestration and consequently enabling the adoption of this pedagogy to the classroom. We present a case study of learning analytics in the context of an ELE supporting the learning of algebra. We focus on the formative qualitative evaluation of a suite of Teacher Assistance tools. We draw conclusions relating to the value of the tools to teachers and reflect with transferable lessons for future related work

Balancing classroom management with mathematical learning: Using practice-based task design in mathematics teacher education

In this paper we present the results from a study conducted in a UK institution in which 21mathematics pre-service teachers engage with two practice-based tasks featuring incidents where classroom management interferes with mathematical learning. We investigate their considerations when they make decisions in classroom situations and how these tasks can trigger their reflections on the teaching and learning of mathematics. In our analysis we used the constructs of social and sociomathematical norms (Cobb & Yackel, 1996) and Teaching Triad (Jaworski, 1994). Results indicate commendable norms pre-service teachers aspire to establish in their classroom, such as peer respect, value of discussion and investigative mathematical learning. However, they often miss the opportunity to engage students with metacognitive discussions and mathematical challenge as they focus on behavioural issues or endorse dichotomous and simplistic views of mathematical learning. We credit these tasks with allowing insight into pre-service teachers’ considerations and we propose their further implementation in teacher education programs