Student Attitudes and Behaviors Towards Digital Textbooks

The purpose of this article is to add to the collective body of knowledge on student behavior and attitudes relative to the adoption of digital textbooks. The article summarizes an ongoing research project that examines past, current and evolving behavior in the classroom related to digital textbooks and school. It includes students, faculty and administrative attitudes behaviors and perceptions. This research was undertaken at the Sawyer Business School of Suffolk University in Boston, Massachusetts. Student attitudes and behavior toward their use of digital textbooks (eTextbooks) in higher education was examined in an ongoing longitudinal study over two years at Sawyer Business School, Suffolk University. Students in the class were divided into six teams. Five of the teams were assigned an eTextbook device and the sixth team was given a paper textbook for use through the semester. The digital technologies examined were: Amazon Kindle, Sony eReader Touch, Apple iPad, enTourage eDGe, and CourseSmart. Student attitudes and behaviors were examined pre and post class by survey each semester, and during the semesters through quizzes, journals and classroom discussion. Differential learning was measured between the six teams. Student attitudes and behaviors are becoming more receptive to and accepting of using digital textbooks each year. There was no significant difference in learning between the eTextbook devices teams or between them and the paper textbook team.     

One World Publishing,Brought to You by the Internet

The migration from print books to ebooks is more than a change of format; it is also the first step in an ongoing process, whose final outcome is hard to predict. Ebooks are likely to lead to a restructuring of the industry by enabling cross-border commerce. This in turn is likely to lead to difficult disputes over territorial rights. It appears probable that these disputes will be resolved by an assertion of the dominance of the American market and the publishers that already serve it well, as authors are likely to place their rights with practitioners in the largest markets. This in turn will lead to the acquisition of many smaller “national” publishers, which cannot compete on a world stage with truly global publishers. But rather than simply becoming sources of editorial product for American-based global marketing machines, smaller publishers operating in different regions will respond through innovation, both in product design (attempting to do electronically what cannot be done in print) and in developing new marketing plans that the giant publishers would be indisposed to pursue.     

In from the Edge: The Progressive Evolution of Publishing in the Age of Digital Abundance

The forces for change in the 600 hundred-year history of book publishing have never been more powerful and fundamental than in 2011. Barely 12 months ago, what publishers viewed as “innovation” was the creation of digitized versions of physical books to be ‘consumed’ on e-reading devices. As 2011 begins, that change is largely regarded as accepted business practice, and the edge of “innovation” is moving in more complex directions. Publishing finds itself in the midst of a ‘phase shift’ from the scarcity model of print to a complex, new world of digital abundance. The dimensions of change, moreover, its speed, and its extent are still unknown. While book publishing begins with the creative work of authors, digital technologies are turning the business models inside out. Among the forces for change acting on book publishing, this article examines several phenomena that are working their way in from the edge to the center of the industry, including complex interwoven considerations around container, context, and customer.     

The sum of its parts: reducing sparsity in click estimation with query segments

The critical task of predicting clicks on search advertisements is typically addressed by learning from historical click data. When enough history is observed for a given query-ad pair, future clicks can be accurately modeled. However, based on the empirical distribution of queries, sufficient historical information is unavailable for many query-ad pairs. The sparsity of data for new and rare queries makes it difficult to accurately estimate clicks for a significant portion of typical search engine traffic. In this paper we provide analysis to motivate modeling approaches that can reduce the sparsity of the large space of user search queries. We then propose methods to improve click and relevance models for sponsored search by mining click behavior for partial user queries. We aggregate click history for individual query words, as well as for phrases extracted with a CRF model. The new models show significant improvement in clicks and revenue compared to state-of-the-art baselines trained on several months of query logs. Results are reported on live traffic of a commercial search engine, in addition to results from offline evaluation.     

Variational bayes for modeling score distributions

Empirical modeling of the score distributions associated with retrieved documents is an essential task for many retrieval applications. In this work, we propose modeling the relevant documents’ scores by a mixture of Gaussians and the non-relevant scores by a Gamma distribution. Applying Variational Bayes we automatically trade-off the goodness-of-fit with the complexity of the model. We test our model on traditional retrieval functions and actual search engines submitted to TREC. We demonstrate the utility of our model in inferring precision-recall curves. In all experiments our model outperforms the dominant exponential-Gaussian model.     

Retrieval constraints and word frequency distributions a log-logistic model for IR

We first present in this paper an analytical view of heuristic retrieval constraints which yields simple tests to determine whether a retrieval function satisfies the constraints or not. We then review empirical findings on word frequency distributions and the central role played by burstiness in this context. This leads us to propose a formal definition of burstiness which can be used to characterize probability distributions with respect to this phenomenon. We then introduce the family of information-based IR models which naturally captures heuristic retrieval constraints when the underlying probability distribution is bursty and propose a new IR model within this family, based on the log-logistic distribution. The experiments we conduct on several collections illustrate the good behavior of the log-logistic IR model: It significantly outperforms the Jelinek-Mercer and Dirichlet prior language models on most collections we have used, with both short and long queries and for both the MAP and the precision at 10 documents. It also compares favorably to BM25 and has similar performance to classical DFR models such as InL2 and PL2.     

Managing the Progressive Publishing Company During Market and Technology Transitions

As new media technologies and platforms emerge and take hold in our society, traditional publishers are wondering: What’s in this new content climate for me? The simple answer is: a lot. The digital world, mobile content delivery mechanisms and the public’s increasing comfort—even preference for—a media menu from which they can pick and choose what they want and how they want to receive it, brings exciting and potentially lucrative opportunities. For publishers who understand how to leverage their brand and create authentic, identifiable value in the eyes of the customer, risk can be reduced and new revenue streams built. Here are four best practices to position your publishing company for growth.     

Popular E-Content at The New York Public Library: Successes and Challenges

Updated from a presentation given at Biblionext.it in Rome in April 2011, this article will highlight The New York Public Library’s success with e-books and other forms of popular e-content and our efforts to stay one step ahead of the consumer shift from print reading to e-reading. Consumer e-reading is dominated by Amazon.com in the US, followed by one of the largest chain bookstores, BarnesandNoble.com. The availability of digital versions of very popular titles, coupled with the explosion of e-readers, tablets, and smartphones that are priced competitively and fairly easy to use, are helping move a lot of Americans into the e-book world. Last month, Amazon.com announced they sold more e-books than physical books for the first time ever. Print books are not going away, but our experience is that it is clear e-books are no longer just an extra format to offer, they are integral to our future.     

Is there an ethics of algorithms?

We argue that some algorithms are value-laden, and that two or more persons who accept different value-judgments may have a rational reason to design such algorithms differently. We exemplify our claim by discussing a set of algorithms used in medical image analysis: In these algorithms it is often necessary to set certain thresholds for whether e.g. a cell should count as diseased or not, and the chosen threshold will partly depend on the software designer’s preference between avoiding false positives and false negatives. This preference ultimately depends on a number of value-judgments. In the last section of the paper we discuss some general principles for dealing with ethical issues in algorithm-design.