AnswerTree – a hyperplace-based game for collaborative mobile learning

In this paper we present AnswerTree, a collaborative mobile location-based educational game designed to teach 8-12 year olds about trees and wildlife within the University of Nottingham campus. The activity is designed around collecting virtual cards (similar in nature to the popular Top TrumpsTM games) containing graphics and information about notable trees. Each player begins by collecting one card from a game location, but then he or she can only collect further cards by answering questions – whose solutions are obtainable through sharing knowledge with other cardholders. This ostensibly allows each player to become a subject expert at the start of the game, encouraging collaborative interaction for the game to be successfully completed. In this initial paper we will outline the structure and background of this location based game. AnswerTree has been authored within the Hyperplace framework, and is a first implementation of a wider process to develop a flexible, multi-purpose platform for both individual and group location-based mobile learning

Contextual Media Retrieval Using Natural Language Queries

The widespread integration of cameras in hand-held and head-worn devices as well as the ability to share content online enables a large and diverse visual capture of the world that millions of users build up collectively every day. We envision these images as well as associated meta information, such as GPS coordinates and timestamps, to form a collective visual memory that can be queried while automatically taking the ever-changing context of mobile users into account. As a first step towards this vision, in this work we present Xplore-M-Ego: a novel media retrieval system that allows users to query a dynamic database of images and videos using spatio-temporal natural language queries. We evaluate our system using a new dataset of real user queries as well as through a usability study. One key finding is that there is a considerable amount of inter-user variability, for example in the resolution of spatial relations in natural language utterances. We show that our retrieval system can cope with this variability using personalisation through an online learning-based retrieval formulation.Comment: 8 pages, 9 figures, 1 tabl

A Mobile-Based Group Quiz System to Promote Collaborative Learning and Facilitate Instant Feedback

In this paper we develop and evaluate a mobile-based questioning-answering system (MQAS) that complements traditional learning which can be used as a tool to encourage teachers to give their students mobile-based weekly group quizzes. These quizzes can provide teachers with valid information about the progress of their students and can also motivate students to work in a collaborative manner in order to facilitate the integration of their knowledge. We describe the architecture and experiences with the system

Learning to Rank Question-Answer Pairs using Hierarchical Recurrent Encoder with Latent Topic Clustering

In this paper, we propose a novel end-to-end neural architecture for ranking candidate answers, that adapts a hierarchical recurrent neural network and a latent topic clustering module. With our proposed model, a text is encoded to a vector representation from an word-level to a chunk-level to effectively capture the entire meaning. In particular, by adapting the hierarchical structure, our model shows very small performance degradations in longer text comprehension while other state-of-the-art recurrent neural network models suffer from it. Additionally, the latent topic clustering module extracts semantic information from target samples. This clustering module is useful for any text related tasks by allowing each data sample to find its nearest topic cluster, thus helping the neural network model analyze the entire data. We evaluate our models on the Ubuntu Dialogue Corpus and consumer electronic domain question answering dataset, which is related to Samsung products. The proposed model shows state-of-the-art results for ranking question-answer pairs.Comment: 10 pages, Accepted as a conference paper at NAACL 201

EU - Information and Communication Technology (ICT) and e-learning in Education Project - Phase II

The training needs analysis was conducted beteeen February and April 2015 for the EU funded project: ICT in Education in Kosovo. The processes required to perform the traning needs analysis have been. The design of a framework of competences; The identification of target groups; The creation and implementation of an online survey to assess the competence of education sector personnel against the competences contained in the framework; The collation, preparation and analysis of the survey data; and Reporting the research findings.European Union Office in KosovoEuropeAid/133846/C/SER/X