The Librarian BFF: A Case Study of a Cohort-Based Personal Librarian Program

This case study presents the development and implementation of a personal librarian program for a cohort-based, executive-style higher education administration doctoral program. Librarians and the program director collaborated to create a student-centered program based on individual research needs. The personal librarian program was designed to build a close relationship between the librarian and individual students; to help identify their research knowledge gaps; and to identify resources to meet each individual students' research needs.     

The Formation of Swedish Media Studies, 1960–1980

Around 1960, the politics of the emerging media society in Sweden tended to fixate the formative functions of mass communication. The monopoly of public service broadcast media, press subsidies and new tendencies in film policy were some of the issues around which uncertainty prevailed. New methods to provide reliable data were sought by politicians, since empirical facts were required as arguments for an updated media policy. This article examines the different ways that the field of media studies was introduced in Sweden between 1960 and 1980. We argue that Swedish academic media studies departed from, and emerged within, a rather diffuse borderland between industry, politics and academia. The formation of national media research in Sweden can partly be seen as an effect of politicians and the media industry wanting to be better informed on issues such as media influence, media ownership and the habits and composition of the media audience.     

Applying LDA Topic Modeling in Communication Research: Toward a Valid and Reliable Methodology

ABSTRACT

Latent Dirichlet allocation (LDA) topic models are increasingly being used in communication research. Yet, questions regarding reliability and validity of the approach have received little attention thus far. In applying LDA to textual data, researchers need to tackle at least four major challenges that affect these criteria: (a) appropriate pre-processing of the text collection; (b) adequate selection of model parameters, including the number of topics to be generated; (c) evaluation of the model’s reliability; and (d) the process of validly interpreting the resulting topics. We review the research literature dealing with these questions and propose a methodology that approaches these challenges. Our overall goal is to make LDA topic modeling more accessible to communication researchers and to ensure compliance with disciplinary standards. Consequently, we develop a brief hands-on user guide for applying LDA topic modeling. We demonstrate the value of our approach with empirical data from an ongoing research project.     

Granularity of algorithmically constructed publication-level classifications of research publications: Identification of topics

The purpose of this study is to find a theoretically grounded, practically applicable and useful granularity level of an algorithmically constructed publication-level classification of research publications (ACPLC). The level addressed is the level of research topics. The methodology we propose uses synthesis papers and their reference articles to construct a baseline classification. A dataset of about 31 million publications, and their mutual citations relations, is used to obtain several ACPLCs of different granularity. Each ACPLC is compared to the baseline classification and the best performing ACPLC is identified. The results of two case studies show that the topics of the cases are closely associated with different classes of the identified ACPLC, and that these classes tend to treat only one topic. Further, the class size variation is moderate, and only a small proportion of the publications belong to very small classes. For these reasons, we conclude that the proposed methodology is suitable to determine the topic granularity level of an ACPLC and that the ACPLC identified by this methodology is useful for bibliometric analyses.     

Investigating the quality of interactions and public engagement around scientific papers on Twitter

This study explores science communication on Twitter by investigating a sample of tweets referring to academic papers in five different scientific fields. The specifications of science communicators on Twitter, the characteristics of those who initiate actions (by tweeting), the extent and quality of reactions (retweeting), individual and group interactions, and the distribution of tweets across types of engagement in the process of science communication (i.e., dissemination, consultation, and evaluation) were explored. A broad array of actors is involved in the communication of science on Twitter, with individual citizens and individual researchers playing an important role. In principle, this is promising for creating direct interaction, which can be difficult through more traditional mass media. The vast majority of communication activities regarding academic papers is undigested dissemination with almost no sign of debate, contestation, or collective reflection. Another general finding of this study is that bot accounts play a major role in the science communication landscape on Twitter.     

Young Children’s Ability to Produce Valid and Relevant Counter-Arguments

In collaborative problem solving, children produce and evaluate arguments for proposals. We investigated whether 3- and 5-year-olds (N = 192) can produce and evaluate arguments against those arguments (i.e., counter-arguments). In Study 1, each child within a peer dyad was privately given a reason to prefer one over another solution to a task. One child, however, was given further information that would refute the reasoning of their partner. Five-year-olds, but not 3-year-olds, identified and produced valid and relevant counter-arguments. In Study 2, 3-year-olds were given discourse training (discourse that contrasted valid and invalid counter-arguments) and then given the same problem-solving tasks. After training, 3-year-olds could also identify and produce valid and relevant counter-arguments. Thus, participating in discourse about reasons facilitates children’s counter-argumentation.     

The Semiotics of Learning New Words

In several of his papers, Charles S. Peirce illustrates processes of interpreting and understanding signs by examples from second language vocabulary teaching and learning. The insights conveyed by means of these little pedagogical scenarios are not meant as contributions to the psychology of second language learning, but they aim at elucidating fundamental semiotic implications of knowledge acquisition in general. Peirce's semiotic premise that a well‐understood sign is one that represents an object and creates an interpretant is essential to the understanding of how new words and signs in general can be taught and learned. The article argues that Peirce's theory of the object of the sign, especially of the necessity of collateral experience of the object of a sign, can help to understand the riddle posed by of the Meno paradox of the impossibility of learning what we do not yet know. It examines the semiotic implications of the didactic methods of teaching and learning through translation, ostension, mental and real images, as well as metacognition, and it shows how icons, indices, and symbols are essential to learning new words.     

Course Design,Quality Matters Training,and Student Outcomes

ABSTRACT

North Carolina Central University (NCCU) recognized the need to address the increasing rates of Ds, Fs, and Withdrawal by students matriculating in online courses. Led by two science faculty, a faculty learning community in partnership with the NCCU Division of Extended Studies was created to assess online science course offerings and instruction. Faculty within this learning community completed the Quality Matters (QM) “Applying the Quality Matters Rubric” course. This online training course, coupled with services provided by the NCCU Division of Extended Studies, offered the faculty learning community a variety of pedagogical strategies to meet their instructional needs. All faculty participating in this learning community completed the online training course and all faculty indicated that they implemented changes in their subsequent online course offerings. This article describes the impact of that training and the application of quality course design standards in the Quality Matters Rubric on the design and student outcomes for an Introductory Biology course over four terms. As faculty learning communities are broadly utilized, it is anticipated that this article may present an effective strategy to increase the quality and quantity of online science, technology, engineering and mathematics (STEM) courses at similar institutions.