Constructivist theory as a foundation for the utilization of digital technology in the lifelong learning process

Lifelong learning, with the help of digital technology, possesses the capacity to offer individual significant advantages to individual learners. This paper examines both the diverse approaches to lifelong learning and the digital tools available to promote these strategies. The paper contains a review of some of the main articles pertaining to the fields of constructivism, digital technology, and the process of lifelong learning. Specifically, the authors intend to critically evaluate the utilization of rapidly developing digital technologies, such as computers, tablets, and mobile devices, within lifelong learning and their role as tools in promoting access to both practical and theoretical knowledge and in facilitating the communication of ideas within a global network, as per the constructivist approach. Hence, this article relies upon a specific definition of lifelong learning and an exploration of the notional foundation of what comprises lifelong learning and the environment in which their knowledge acquisition occurs. Thus, a framework for the present research is established wherein peer-reviewed studies concerning the use of social media by lifelong learners is explored, and extrapolating from the dual tenets of professional development and adult learning theory. Moreover, the authors additionally examine approaches to the notion of PLEs (personal learning environments) and PLNs (personal learning networks) as related to the selection of relevant lifelong learning strategies. The discussion is exemplified by cases ranging from video platforms to blogs and is simultaneously multidisciplinary and spanning diverse fields. Each example has applicability for lifelong learning and represents the characteristics of constructivism and its support within a web-based learning environment. It is thereby suggesting that effective and meaningful strategies supportive of the lifelong learning lifestyle can be achieved via well- designed PLEs and PLNs

Evaluating the use of user content feed swapping for counteracting filter bubbles

Abstract. The term filter bubble refers to a phenomenon in which a recommendation system fails to offer diverse or novel content, and instead offers content that reinforces particular belief systems. Filter bubbles are considered harmful when they restrict users’ exposure to diverse content and thereby reinforce potentially harmful or misinformed ideologies, contribute to the spread of misinformation, and foster the creation of echo chambers. This thesis proposes a solution to counteract the effects of filter bubbles by providing users with the option to switch content feeds with their least similar users’ feed. The solution was achieved by substituting the correlation coefficient used in collaborative filtering recommendation systems. An application was developed to simulate post recommendations for users, initially employing a traditional collaborative filtering system. This was then followed by a collaborative filtering system that recommended posts based on the likes of the least similar user to the current user. User engagement metrics and cognitive mapping metrics were used to evaluate this solution. If the solution did not negatively affect user engagement and demonstrated an ability to increase the diversity of users’ bias perception and promote a more nuanced understanding of bias within the social media application, it met the requirements of these metrics. There was an overall increase in user engagement after the users’ feed was swapped. Moreover, the users’ perception of bias became more diversified, indicating that the solution prompted a broader awareness of bias within the social media application users were engaging with. Based on these results, the proposed solution was deemed as potentially effective in addressing the filter bubble problem. The solution’s viability was established solely within a simulated environment. To determine its real-world applicability, it requires further testing in a naturalistic environment with more participants

Text-based Sentiment Analysis and Music Emotion Recognition

Nowadays, with the expansion of social media, large amounts of user-generated texts like tweets, blog posts or product reviews are shared online. Sentiment polarity analysis of such texts has become highly attractive and is utilized in recommender systems, market predictions, business intelligence and more. We also witness deep learning techniques becoming top performers on those types of tasks. There are however several problems that need to be solved for efficient use of deep neural networks on text mining and text polarity analysis. First of all, deep neural networks are data hungry. They need to be fed with datasets that are big in size, cleaned and preprocessed as well as properly labeled. Second, the modern natural language processing concept of word embeddings as a dense and distributed text feature representation solves sparsity and dimensionality problems of the traditional bag-of-words model. Still, there are various uncertainties regarding the use of word vectors: should they be generated from the same dataset that is used to train the model or it is better to source them from big and popular collections that work as generic text feature representations? Third, it is not easy for practitioners to find a simple and highly effective deep learning setup for various document lengths and types. Recurrent neural networks are weak with longer texts and optimal convolution-pooling combinations are not easily conceived. It is thus convenient to have generic neural network architectures that are effective and can adapt to various texts, encapsulating much of design complexity. This thesis addresses the above problems to provide methodological and practical insights for utilizing neural networks on sentiment analysis of texts and achieving state of the art results. Regarding the first problem, the effectiveness of various crowdsourcing alternatives is explored and two medium-sized and emotion-labeled song datasets are created utilizing social tags. One of the research interests of Telecom Italia was the exploration of relations between music emotional stimulation and driving style. Consequently, a context-aware music recommender system that aims to enhance driving comfort and safety was also designed. To address the second problem, a series of experiments with large text collections of various contents and domains were conducted. Word embeddings of different parameters were exercised and results revealed that their quality is influenced (mostly but not only) by the size of texts they were created from. When working with small text datasets, it is thus important to source word features from popular and generic word embedding collections. Regarding the third problem, a series of experiments involving convolutional and max-pooling neural layers were conducted. Various patterns relating text properties and network parameters with optimal classification accuracy were observed. Combining convolutions of words, bigrams, and trigrams with regional max-pooling layers in a couple of stacks produced the best results. The derived architecture achieves competitive performance on sentiment polarity analysis of movie, business and product reviews. Given that labeled data are becoming the bottleneck of the current deep learning systems, a future research direction could be the exploration of various data programming possibilities for constructing even bigger labeled datasets. Investigation of feature-level or decision-level ensemble techniques in the context of deep neural networks could also be fruitful. Different feature types do usually represent complementary characteristics of data. Combining word embedding and traditional text features or utilizing recurrent networks on document splits and then aggregating the predictions could further increase prediction accuracy of such models

High school students’ social media usage : an application on user behaviors, preferences and reasons based on the uses and gratifications theory

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Günümüz dünyasında, insanlar ve kitle iletişim araçları arasında etkileşimli bir iletişim süreci vardır. Bireylerin birbirleriyle etkileşim içinde oldukları yeni medya teknolojileri türüne sosyal medya denir. Bu anlamda zamanlarının çoğunu sosyal medyada geçiren bireyler günlük yaşamlarının yanı sıra çevrimiçi bir yaşam da sürdürürler. Sosyal medyadan en çok zaman geçiren ve etkilenen gruplardan biri de lise öğrencileridir diyebiliriz. Bu nedenle, bu çalışma Eskişehir'deki lise öğrencilerinin sosyal medya kullanım motivasyonlarını Kullanımlar ve Doyumlar Kuramı çerçevesinde belirlemeyi amaçlamaktadır. Anket ile yapılan araştırmada, 445 kullanıcıya hazırlanan ölçek soruları soruldu. Çalışmada, nicel veri toplama tekniklerinden biri olan anket uygulanmış olup, elde edilen veriler Statistical Package for the Social Sciences (SPSS) programı ile yorumlanmıştır. Elde edilen veriler kodlama yöntemiyle çözümlenmiştir. Faktör analizi ile 5 farklı kullanım ve memnuniyet saptanmıştır. Bunlar Eğlenme ve Rahatlama Motivasyonu, Sosyal Etkileşim Motivasyonu, Gözlem ve Rehberlik Motivasyonu, Karar Verme-Bilgi Motivasyonu ve Kişisel Sunum Motivasyonu olarak sıralanabilir. Bazı kullanıcıların demografik özellikleri ve sosyal medya kullanım biçimleri, farklı kullanımlar ve memnuniyetlerle ilişkilendirilmiştir.In today's world, there is an interactive communication process between people and mass media.The type of new media technologies or courses through which individuals interact each other is called social media. In this sense, individuals who spend most of their time on social media courses have constructed an online life apart their daily lives. One of the most influenced groups by social media is high school students. Therefore, this study aims to determine the motivations of social media usage of high school students in Eskisehir within the framework of Uses and Gratifications Theory. In the research conducted with the questionnaire, 445 users prepared scale questions were asked. The questionnaire, which is one of the quantitative data collection techniques, is applied and, the obtained data is interpreted through the Statistical Package for the Social Sciences (SPSS) program. The data obtained were interpreted by coding. Factor analysis revealed 5 different uses and gratificaiton. These can be listed as Recreation and Relaxation Motivation, Social Interaction Motivation, Observation and Guidance Motivation, Decision-Making-Information Motivation and, Personal Presentation Motivation. Some user demographics and social media usage patterns have been associated with different uses and gratifications

Where can teens find health information? A survey of web portals designed for teen health information seekers

The Web is an important source for health information for most teens with access to the Web (Gray et al, 2005a; Kaiser, 2001). While teens are likely to turn to the Web for health information, research has indicated that their skills in locating, evaluating and using health information are weak (Hansen et al, 2003; Skinner et al, 2003, Gray et al, 2005b). This behaviour suggests that the targeted approach to finding health information that is offered by web portals would be useful to teens. A web portal is the entry point for information on the Web. It is the front end, and often the filter, that users must pass through in order to link to actual content. Unlike general search engines such as Google, content that is linked to a portal has usually been pre-selected and even created by the organization that hosts the portal, assuring some level of quality control. The underlying architecture of the portal is structured and thus offers an organized approach to exploring a specific health topic. This paper reports on an environmental scan of the Web, the purpose of which was to identify and describe portals to general health information, in English and French, designed specifically for teens. It answers two key questions. First of all, what portals exist? And secondly, what are their characteristics? The portals were analyzed through the lens of four attributes: Usability, interactivity, reliability and findability. Usability is a term that incorporates concepts of navigation, layout and design, clarity of concept and purpose, underlying architecture, in-site assistance and, for web content with text, readability. Interactivity relates to the type of interactions and level of engagement required by the user to access health information on a portal. Interaction can come in the form of a game, a quiz, a creative experience, or a communication tool such as an instant messaging board, a forum or blog. Reliability reflects the traditional values of accuracy, currency, credibility and bias, and in the web-based world, durabililty. Findability is simply the ease with which a portal can be discovered by a searcher using the search engine that is most commonly associated with the Web by young people - Google - and using terms related to teen health. Findability is an important consideration since the majority of teens begin their search for health information using search engines (CIBER, 2008; Hansen et al, 2003). The content linked to by the portals was not evaluated, nor was the portals’ efficacy as a health intervention. Teens looking for health information on the Web in English have a wide range of choices available but French-language portals are much rarer and harder to find. A majority of the portals found and reviewed originated from hospitals, associations specializing in a particular disease, and governmental agencies, suggesting that portals for teens on health related topics are generally reliable. However, only a handful of the portals reviewed were easy to find, suggesting that valuable resources for teens remain buried in the Web

Problematizing the digital literacy paradox in the context of older adults’ ICT use: Aging, media discourse, and self-determination

Despite evidence of an upward trend in ICT adoption, current media discourse suggests that older adults (those 60+) lag behind in terms of engagement with digital technology. Through a survey and interviews with older adults we investigate how this population views their own digital skills, barriers to digital literacy, and the social and institutional support system they draw on for technology help. Older adults recognize their age as a factor in the adoption of technology and note differences between how they and younger generations use technology. A lack of skills and limited social and institutional support make it difficult for older adults to gain experience and comfort with technology. However, support systems, such as family and peers, can help mediate older adults’ reluctance with technology. We propose a model with the aim of understanding the needs of older adults in gaining greater digital literacy