Reporting Mobile Social Media Use: How Survey and Experience Sampling Measures Differ

Quantifying the ubiquitous, ephemeral, and highly diverse patterns of mobile social media (MSM) use is a challenge for communication research. Most researchers employ retrospective survey measurement, thus depending on the accuracy of users’ memories and generalizations. Alternatively, some researchers rely on in-situ measurement, being less dependent on users’ memories and generalizations, but requiring random situation samples. To assess differences and similarities between these two measurement approaches we analyzed whether characteristics (duration and frequency of a usage episode, habit, elaboration, and gratifications) of MSM use (regarding Facebook, WhatsApp, and YouTube) vary between retrospective survey and mobile experience sampling measurement. We observe a consistent pattern of higher estimates in retrospect as compared to individual averages of in-situ reports. The absolute magnitude of these differences varies considerably between platforms and characteristics studied. Nonetheless, for most constructs and platforms we find low significant positive correlations between retrospective and aggregated in-situ values.     

Optimal design for manipulation of random consensus over discrete information in networked systems

In distributed and cooperative systems, the network structure is determinant to the success of the strategy adopted to solve complex tasks. Those systems are primarily governed by consensus protocols whose convergence is intrinsically dependent on the network topology. Most of the consensus algorithms deal with continuous values and perform average-based strategies to reach cohesion over the exchanged information. However, many problems demand distributed consensus over countable values, that cannot be handled by traditional protocols. In such a context, this work presents an approach based on semidefinite programming to design the optimal weights of a network adjacency matrix, in order to control the convergence of a distributed random consensus protocol for variables at the discrete-space domain, based on the voter model. As a second contribution, this work uses Markov theory and the biological inspiration of epidemics to find out a dynamical spreading model that can predict the information diffusion over this discrete consensus protocol. Also, convergence properties and equilibrium points of the proposed model are presented regarding the network topology. Finally, extensive numerical simulations evaluate the effectiveness of the proposed consensus algorithm, its spreading model, and the approach for optimal weight design.     

An unsupervised heuristic-based approach for bibliographic metadata deduplication

Digital libraries of scientific articles contain collections of digital objects that are usually described by bibliographic metadata records. These records can be acquired from different sources and be represented using several metadata standards. These metadata standards may be heterogeneous in both, content and structure. All of this implies that many records may be duplicated in the repository, thus affecting the quality of services, such as searching and browsing. In this article we present an approach that identifies duplicated bibliographic metadata records in an efficient and effective way. We propose similarity functions especially designed for the digital library domain and experimentally evaluate them. Our results show that the proposed functions improve the quality of metadata deduplication up to 188% compared to four different baselines. We also show that our approach achieves statistical equivalent results when compared to a state-of-the-art method for replica identification based on genetic programming, without the burden and cost of any training process.     

On Rest-from-Deliberate-Learning as a Mechanism for the Spacing Effect: Commentary on Chen et al. (2021)

Educational Psychology Review - In their recent paper, Chen et al. (Educational Psychology Review, 2021) propose that rest periods between deliberate learning characterize the spacing effect and...     

The changing role of the secondary principal in the United States: An historical perspective

This paper reviews the historical development of the secondary principalship in the US and examines how the current role of the principal is a result of historical forces. The authors consider a preferred future for the principalship and present recommendations for change.     

Using Simulation and Patient Role Play to Teach Electrocardiographic Rhythms to Physical Therapy Students

Purpose

The aims of the study were to differentiate: (1) physical therapy (PT) students’ preferred method for learning electrocardiographic (ECG) recognition utilizing standardized patient (SP) and human patient simulation (HPS) approaches, (2) the impact of HPS or SP on confidence in interpreting ECG, and 3) the effect of HPS or SP on students’ ability to make clinical decisions based upon ECG interpretation.

Methods

“Three educational methods were employed to teach ECG recognition to two different years of novice PT students enrolled in a cardiopulmonary physical therapy class. First, all students had a traditional lecture on ECG. Following the lecture, two problem-based learning (PBL) approaches were utilized. One approach used a SP and paper ECG strips, and the second approach utilized HPS with simulated ECG monitoring.”¹ Following the two PBL approaches, a post instructional survey regarding the learning experiences was conducted. Following instruction, each cohort (n = 24, n = 29) of PT students was given a mixed methods survey about their experience.

Results

Survey return rate amongst both cohorts was 77%. Independent sample of individual cohort and paired t-tests of combined data comparing HPS to SP revealed a strong preference for HPS (p = 0.003 (2008 cohort) and p = 0.0001 (2010 cohort)) and combined cohort (p = 0.0001). There were no significant differences in responses between cohorts or preference between the HPS method and the use of SP and HPS combined. Additionally, 75% of respondents either strongly agreed or agreed that they felt confident with their skill in ECG interpretation as presented with HPS or SP. 90% either strongly agreed or agreed that they understood how the ECG relates to patient treatment. Summative assessment utilizing HPS revealed that students were competent in their performance in ECG recognition and clinical decision making related to patient treatment.¹

Conclusion

Data support that HPS was the preferred method to improve student confidence in ECG recognition and interpretation.Key Words: human patient simulation, electrocardiography, critical care management, educational technology