Twitter news-in-education platform for social, collaborative, and flipped learning

Abstract

NIE (newspaper in education), which is the study utilizing newspaper-based educational resources in the classroom, has been pursued for a long time. Traditional NIE allows only one-way interaction and available media are limited. In addition, it has difficulty in capturing the latest "hot" issues or recognizing public opinions. In this paper, we propose a platform called TNIE (Twitter news in education) that utilizes Twitter in NIE. TNIE has many advantages compared to traditional NIE: (1) it classifies the latest news into various topics, (2) the classified news content can be browsed effectively via a hierarchical visualization scheme, and (3) effective discussion or debate groups can be easily formed based on the learners' news selection. To evaluate the performance of our scheme, we implemented a prototype system and performed several experiments. According to the results, our news classification scheme achieved an 87.8 % F-measure on average, which is superior to the 78.94 % of previous studies. We also had volunteers use our prototype system and evaluate its main functions, e.g., news visualization, classification, learner clustering, and collaborative learning. We report some of these evaluation results. This paper is an extended version of our conference paper [30].

Tag Recommendation by Word-Level Tag Sequence Modeling

“…From Table 9, we can see that meaningless tags rarely appear in the generated tag sequences, and using the N-best voting strategy can reduce the error rates effectively. In Table 9, 1,076,588 in #Outputs column is the total number of N-best (N = 48) outputs of our model, so it is significantly larger than the number of the input Zhihu questions (8,946) and with many wrong predictions (11,814). After using N-best voting, most unconfident predictions are removed, and thus achieving a very low error rate (0.03%).…”

“…These corpora contain a form of metadata tags marking its keywords or topics. These tags are useful in many real-world applications, e.g., information retrieval [5,17,1], sentiment analysis [2,10], hot issues discovery [21,11], public opinion analyses [14,15], to name a few. Therefore, automatic tag recommendation has gained a lot of research interests recently.…”

Constructing Differentiated Educational Materials Using Semantic Annotation for Sustainable Education in IoT Environments

“…However, they did not consider the popularity of the news nor did they mention how to select the appropriate news from among the news sources for learners. In our previous studies [30,31], we proposed a platform called TNIE (Twitter News in Education) that utilizes Twitter in NIE. In this study, Twitter news was classified according to its topic and classified news topics were provided to learners through various visualization tools.…”

“…Twitter is a popular online news and social network service where users can post and interact with messages of up to 140 characters (termed tweets) to each other [32]. A large amount of news is generated every second on Twitter and disseminated quickly to the public [30]. However, owing to the size limitation of Twitter news, it has difficulty in delivering detailed information.…”

Actitudes docentes hacia la integración curricular de la prensa digital en los centros escolares de Educación Obligatoria

“…En relación al alumnado, conviene atender aquellas actividades en el aula que implican la lectura de noticias en Internet (Singer y Alexander, 2016;Kim, Hwang y Rho, 2016;Digital NIE, 2007). Así como la creación de prensa electrónica escolar (Mena, 2016;Trillo, 2003;Canavilhas, Merino-Arribas y Kroth, 2016) por tratarse de una actividad que permite implicar a toda la comunidad educativa aprovechando las ventajas didácticas de la «galaxia mediática» (Cabero y Aguaded, 2014: 70).…”