Neural information retrieval: at the end of the early years

A recent “third wave” of neural network (NN) approaches now delivers state-of-the-art performance in many machine learning tasks, spanning speech recognition, computer vision, and natural language processing. Because these modern NNs often comprise multiple interconnected layers, work in this area is often referred to as deep learning. Recent years have witnessed an explosive growth of research into NN-based approaches to information retrieval (IR). A significant body of work has now been created. In this paper, we survey the current landscape of Neural IR research, paying special attention to the use of learned distributed representations of textual units. We highlight the successes of neural IR thus far, catalog obstacles to its wider adoption, and suggest potentially promising directions for future research.     

Look who’s talking: Emergent evidence for discriminating between differences in listserv participation

This paper reports findings from a study of LookJed, the oldest and largest on-line forum for Computer Mediated Discussion among individuals interested in Jewish education. The study adopted a “cyber-ethnographic” approach, with postings to the forum seen as “acts of communication” that reveal what is important to their authors. An interest in exploring similarities between forum conversations and those in teachers’ lounges led to an investigation of Herring’s claim that most listservs do not include discussion at all, only the trading of information. This investigation found that active forum participants generally use the forum for discrete purposes, most commonly to exchange information about “subject matter” or “teaching material”, less commonly to exchange opinions and ideas, and rarely to do both. Integrating an analysis of patterns of contribution with an examination of their discursive content reveals six preeminent “types” among the population of contributors, each of whom participates in the forum in different ways and acts with different purposes. Although this typology is at best suggestive and needs to be tested against other listserv cases, its easy identification suggests that in order to better understand the cultures of virtual forums, it is important to pursue a more variegated characterization of listserv participants and their motivations than has typically been the case in CMD research where users are most frequently identified as either lurkers or fanatics, or as active or passive participants.     

Teachers’ agency,efficacy, engagement,and emotional resilience during policy innovation implementation

This multiple case study investigated 143 teachers’ responses to focus group questions about their experiences with the simultaneous implementation of three disruptive innovations as part of the U.S. Race-to-the-Top (RTTT) agenda: the Common Core Learning Standards, data-driven instruction, and annual professional performance reviews. We asked: How do teachers describe their experiences implementing these three RTTT innovations? How do teachers describe supports for their adaptation to these innovations? And, for each of these questions, and since the study purposefully included schools with above-predicted student outcomes (i.e. odds-beaters) as well as a comparison set of typically performing schools, we inquired: In what ways do odds-beating school teachers’ experiences differ from their peers in typically performing schools? Guided by an emergent framework that emphasizes the relationships among teacher agency, engagement, efficacy, and emotional resilience and how these vary in different school contexts, findings suggest that district office innovation leadership and resource allocations, school leadership structures and strategies, and collaborative teams and communities of practice vary and relate to teachers’ experiences of innovation implementation. This study advances an empirically-grounded and theoretically rich framework for investigation of teachers’ performance adaptation during policy innovation implementation and suggests implications for future research, policy, and practice.     

Medicare Reimbursement for Counselors: Counseling Professionals’ Advocacy Beliefs and Behavior

The authors analyzed data from 5,528 American Counseling Association members to examine advocacy beliefs and behavior regarding Medicare reimbursement and advocacy for counselors. Nearly half (49.3%) of the respondents had participated in one or more forms of Medicare reimbursement advocacy. Advocacy participation differed significantly by professional status.     

Teaching students to estimate complex probabilities of board game events through simulation

Students are typically introduced to probability through calculating simple events like flipping a coin. While these calculations can be done by hand, more complex probabilistic events, both in class and in the real world, require the use of computers. In this paper, we introduce a new tool—an R shiny web app and associated CRAN package based on the board game “CamelUp”—to help students explore these probability calculations through simulation in a fun context. Through this app and in conjunction with the board game Camel Up, we present some sample activities for helping students better understand and make in-game probabilistic decisions.     

The (De-)evolution of Evolution Games: A Content Analysis of the Representation of Evolution Through Natural Selection in Digital Games

Given the diversity and complexity of education game mechanisms and topics, this article contributes to a theoretical understanding of how game mechanisms “map” to educational topics through inquiry-based learning. Namely, the article examines the presence of evolution through natural selection (ENS) in digital games. ENS is a fundamentally important and widely misunderstood theory. This analysis of ENS portrayal in digital games provides insight into the use of games in teaching ENS. Systematic database search results were coded for the three principles of ENS: phenotypic variation, differential fitness, and fitness heritability. Though thousands of games use the term evolution, few presented elements of evolution, and even fewer contained all principles of ENS. Games developed to specifically teach evolution were difficult to find through Web searches. These overall deficiencies in ENS games reflect the inherent incompatibility between game control elements and the automatic process of ENS.     

The rise of the machines: Artificial intelligence meets scholarly content

Key points

• New forms of human/machine dialogue are emerging as robots understand vast amounts of content rather than simply indexing content as strings of characters.
• Recognizing strings of characters as entities (e.g. = names = authors) allows for meaningful associations between entities and reasoning over these relationships.
• Web‐scale adoption of the Semantic Web approach has been slow because it is too complex to implement and does not scale.
• User intent, discovered through conversational models of human–computer interaction, allows for a deeper understanding of exactly what researchers are looking for.
• Personal agents hold the promise of finding information that we will find useful before we have started to look for it.
• Publishers can use Academic Knowledge APIs to interpret academic user queries and find rich information from the Microsoft Academic Graph.