Rosella Gennari

Children's emotions and quality of products in participatory game design

The paper presents an empirical study centred on a participatory game design activity with 810 years old primary-school children, split in different sessions. The study assesses how children perform in game design and whether they are engaged in design tasks. To this end, the study gathers data concerning the quality of childrens game design products, regarded as indicators of childrens performance in game design. It collects data concerning childrens emotions, which are taken as indicators of their engagement in game design. The paper statistically analyses and discusses how emotions and quality of products evolve across the game design experience, and how emotions are related to childrens quality of products. Results of this work can help researchers, educators and practitioners manage a complex design experience with and for children, and identify key emotions for promoting quality of design work. The paper discusses childrens performance and engagement in participatory game design.It presents a participatory game design study with 810 year olds.The study assesses childrens emotions, for engagement, and product- quality, for performance.The study analyses their correlations, and interpret results with observation data.The paper concludes with implications of the study for participatory game design.

Gamified probes for cooperative learning: a case study

This paper advances the idea of tangible gamified probes for cooperative learning processes, which require synchronous in-presence and in-situ interactions. The paper focuses on gamified probes for promoting a sense of progression and control, as well as social relations in a cooperative learning process in classroom. It reports a case study in a primary school. The study employed gamified probes as early-design solutions: each probe had limited ad-hoc functionalities, tested in the field, and was flexible enough to enable different usages so as to inspire designers. Probes were also endowed with embedded micro-electronic components for enhancing their interaction with children and human-to-human interaction, besides for storing relevant interaction data. After reporting the study results, the paper discusses them, and it concludes reflecting on the design of future gamified probes for enhancing cooperative learning in classroom.

How measuring student performances allows for measuring blended extreme apprenticeship for learning Bash programming

Extreme apprenticeship, a recent learning methodology, was used in a blended fashion for teaching a technical subject: Bash scripting for operating systems. Online learning was supported with the Moodle platform, in particular, for managing Bash programming exercises. How did students behave? Were the exercises equally difficult for them? If not, where did differences arise? And why? This paper reports on the design of a blended learning experience for Bash programming, focusing on the definition and evaluation of levels of programming exercises and on students behavior in programming, supported by Moodle. Many small exercises and few lectures can teach all programming.Measuring student behavior in exercises assesses how they learn.The reported study logged student performances in programming exercises.Metrics were defined for assessing overall programming performances.Data show that all students tend to learn basic programming skills.

Designing games for deaf children: first guidelines

According to the most recent deaf literature, playing with digital games shows positive effects on deaf childrens specific skills. The goal of this paper is to present the first guidelines for the design of games for deaf children. Our review of deaf literature, briefly sketched in the paper, considers such abilities as well as deaf childrens preferences most relevant for the design of digital games for them. Literature findings are then used to compile the guidelines, with accompanying usage examples. Guidelines and literature findings are correlated at the end of this paper.

Supporting Children in Mastering Temporal Relations of Stories: The TERENCE Learning Approach

Though temporal reasoning is a key factor for text comprehension, existing proposals for visualizing temporal information and temporal connectives proves to be inadequate for children, not only for their levels of abstraction and detail, but also because they rely on pre-existing mental models of time and temporal connectives, while in the case of children the system has to induce the development of a mental model not existing yet. Filling this gap was the main goal of the FP7 European project TERENCE, which developed an adaptive learning system shaped around the concepts of repeated interaction experience and of graded text simplification and consistent with consolidated pedagogical approaches built on question-based games. In particular, in this paper the authors present the main features of its learner-oriented read-and-play visual interaction environment that, according to the dual-coding theory, follows a two-tiers approach pairing verbal and visual information.

Challenges in Quality of Temporal Data — Starting with Gold Standards

Information available nowadays in web repositories is big and potentially rich. Natural Language Processing (NLP) systems can play a key role in revealing information: they can analyze and extract relevant information from web content, transforming it into machine-processable annotation data for building knowledge [Campos et al. 2014]. Most state-of-the-art NLP systems are largely based on supervised approaches, that is, machine-learning systems that learn how to analyze content, based on large training texts, referred to as gold standard corpora or, briefly, gold standard. These contain manual annotation data of texts, that is, data manually added by annotation experts. The task of manually annotating a text of a gold standard is hence of paramount importance: since errors in the manual annotation workflow impact the performance of NLP systems, quality control over the annotated data is necessary. Current methods for controlling the quality of annotations are limited: they usually check the local context of the annotation or suggest annotations similar to those already available. A common procedure for keeping annotation data quality under control is the calculation of the so-called interannotator agreement [Artstein and Poesio 2008], a set of statistical measures for computing the agreement of different annotators performing the same task on the same texts: low agreement tends to indicate that the task requires a high degree of personal interpretation or that the annotation guidelines may be poorly written. In spite of existing quality control methods, errors can still be found in

Qualitative Temporal Reasoning Can Improve on Temporal Annotation Quality: How and Why

ABSTRACT The analysis of time helps in extracting knowledge from web contents. In order to analyze massive amounts of data, current natural language processing systems rely mainly on supervised approaches: machine learning algorithms that learn how to classify data based on corpora, annotated with the TimeML mark-up language or one of its derivatives. The quality of annotation data, thus, affects the performances of such systems. Quality can be improved by reasoning on temporal annotations. This article takes such a view. After a review of the strictly necessary background, it focuses on and discusses open issues in the area of quality of temporal annotations: inconsistency and incompleteness of annotations. Then it proposes a semantic reasoning approach as solution for improving on their quality, viz., the SOA-based Qualitative Temporal Reasoner for reasoning about temporal annotations, which leverages on existing theories and tools for qualitative reasoning. The article presents the design of the reasoner and its two main reasoning services: consistency checking for tackling inconsistency, and deduction for addressing incompleteness on demand. Afterward, the paper presents an experimental evaluation of the reasoner, sustaining why the chosen semantic reasoning approach can help improve on quality of annotations. The experiment assesses the reasoner’s performances on two different corpora and from several perspectives, e.g., the effectiveness of consistency checking in terms of the number of inconsistent documents found, and of deduction in terms of the number of annotations added. It concludes with discussion of the results of the evaluation and possible routes for future work.

Achievement Emotions and Peer Acceptance Get Together in Game Design at School

This paper presents a game design experience in primary schools, with children creating game design ideas and prototypes. Children were organized in cooperative groups. Game design tasks were organized following gamification principles, with ad-hoc gamified material. Cooperative learning and gamification served to elicit emotions and social inclusion. This paper measures them as follows. It operationalizes social inclusion with peer acceptance in three different social contexts, measured before and after the game design activity. It tracks achievement emotions experienced during game design at school. Then the paper examines the relationships between achievement emotions and peer acceptance. In this manner, it tackles an open problem in the literature concerning the links between emotions and social well-being in a game design experience. Path analyses indicate that, respectively for received choices and mutual friendships, positive emotions played a significant role in improving children’s social relations, and negative emotions were associated with a significant deterioration of social relations, but only for the extra-school leisure context. The paper concludes assessing the study limits and results in relation to game design with and for children.