Design-based research principles for successful peer tutoring on social media

ABSTRACT

Social media platforms such as WhatsApp are increasingly used in formal education settings. However, there is little research to guide educators on how to set up effective peer tutoring groups on social media platforms, particularly between tutors and tutees who rarely meet face-to-face. In the context of a WhatsApp mathematics tutoring project, we present evidence-based principles to guide the establishment and operation of peer tutoring groups on a social media platform. The development of the principles followed a design-based research framework, based on theories about peer learning, participation barriers to social media use in a low socio-economic setting, and input from participants, who were high school students and university students in Cape Town, South Africa. The refined principles provide guidance for others in similar settings who aim to use tutoring groups on a social media platform to achieve education goals.     

Connecting social perspectives on mathematics teacher education in online environments

This article explores theoretical issues underpinning the design and use of online learning environments in mathematics teacher education. It considers the contribution of social theories of learning to conceptualising technology-mediated interaction, focusing specifically on community of practice models and the notion of digital mathematics performance. The article begins by introducing social perspectives on collaboration. Because of the diversity of theories within this broad research paradigm, the next section outlines networking strategies that have been proposed for connecting theoretical approaches. There follows a discussion of studies that illustrate the community of practice and performance-based approaches to research into online mathematics teacher education. The main purpose of the article is to show how these approaches could be connected by examining the same teaching and learning scenarios through different theoretical lenses. The final section identifies implications of this exploration for the design of online learning environments in mathematics teacher education to capitalise on the affordances of Web-based technologies.     

An evolutionary game theoretic perspective on e-collaboration: The collaboration effort and media relativeness

Studies of e-collaboration from a game-theoretical perspective are practically nonexistent. This article contributes to filling this gap by focusing on the strategic interaction between players as they decide whether and how much to collaborate with each other. We use evolutionary game theory to make predictions about a two-person e-collaboration game. More specifically, we extend the traditional Prisoners’ Dilemma and Snowdrift game theory notions to discrete-strategy e-collaboration games, by explicitly including social punishments into the players’ payoff functions. We also introduce continuous-strategy e-collaboration games with both complete and incomplete information. Finally, we provide two generic dynamic programming models for e-collaboration games with media selection.     

Stochastic semidefinite programming: a new paradigm for stochastic optimization

Semidefinite programs are a class of optimization problems that have been studied extensively during the past 15 years. Semidefinite programs are naturally related to linear programs, and both are defined using deterministic data. Stochastic programs were introduced in the 1950s as a paradigm for dealing with uncertainty in data defining linear programs. In this paper, we introduce stochastic semidefinite programs as a paradigm for dealing with uncertainty in data defining semidefinite programs.The work of this author was supported in part by the U.S. Army Research Office under Grant DAAD 19-00-1-0465. The material in this paper is part of the doctoral dissertation of this author in preparation at Washington State University.     

Game Design as an Interactive Learning Environment for Fostering Students'' and Teachers'' Mathematical Inquiry

Many learning environments, computer-based or not, have been developed for either students or teachers alone to engage them in mathematical inquiry. While some headway has been made in both directions, few efforts have concentrated on creating learning environments that bring both teachers and students together in their teaching and learning. In the following paper, we propose game design as such a learning environment for students and teachers to build on and challenge their existing understandings of mathematics, engage in relevant and meaningful learning contexts, and develop connections among their mathematical ideas and their real world contexts. To examine the potential of this approach, we conducted and analyzed two studies: Study I focused on a team of four elementary school students designing games to teach fractions to younger students, Study II focused on teams of pre-service teachers engaged in the same task. We analyzed the various games designed by the different teams to understand how teachers and students conceptualize the task of creating virtual game learning environment for others, in which ways they integrate their understanding of fractions and develop notions about students' thinking in fractions, and how conceptual design tools can provide a common platform to develop meaningful fraction contexts. In our analysis, we found that most teachers and students, when left to their own devices, create instructional games to teach fractions that incorporate little of their knowledge. We found that when we provided teachers and students with conceptual design tools such as game screens and design directives that facilitated an integration of content and game context, the games as well as teachers' and students' thinking increased in their sophistication. In the discussion, we elaborate on how the design activities helped to integrate rarely used informal knowledge of students and teachers, how the conceptual design tools improved the instructional design process, and how students and teachers benefit in their mathematical inquiry from each others' perspectives. In the outlook, we discuss features for computational design learning environments. This revised version was published online in August 2006 with corrections to the Cover Date.     

Digital game‐based learning for K–12 mathematics education: A meta‐analysis

Digital games (e.g., video games or computer games) have been reported as an effective educational method that can improve students' motivation and performance in mathematics education. This meta‐analysis study (a) investigates the current trend of digital game‐based learning (DGBL) by reviewing the research studies on the use of DGBL for mathematics learning, (b) examines the overall effect size of DGBL on K‐12 students' achievement in mathematics learning, and (c) discusses future directions for DGBL research in the context of mathematics learning. In total, 296 studies were collected for the review, but of those studies, only 33 research studies were identified as empirical studies and systematically analyzed to investigate the current research trends. In addition, due to insufficient statistical data, only 17 out of the 33 studies were analyzed to calculate the overall effect size of digital games on mathematics education. This study will contribute to the research community by analyzing recent trends in significant DGBL research, especially for those who are interested in using DGBL for mathematics education.     

On a Resurgence of Management Simulations and Games

The past few years have seen a significant resurgence of interest in ‘management games’ and ‘management flight simulators’, one particularly active source of such work being the system dynamics community. After proposing a distinction between games and simulations, this paper provides some background to these developments by briefly describing the historical roots of the field and the fundamental ideas of the system dynamics community, which are now giving rise to ‘microworlds’. The training advantages of management simulations and games are then discussed. The paper closes with a note on the research and findings of the system dynamics field and by offering some words of warning on the perils of simulation and game use. Two scenarios for how the use of simulations and games as management education devices might develop in the future are proposed. An Appendix describes five examples of very different types of management simulations and games.     

Extreme logistic regression

Kernel logistic regression (KLR) is a very powerful algorithm that has been shown to be very competitive with many state-of the art machine learning algorithms such as support vector machines (SVM). Unlike SVM, KLR can be easily extended to multi-class problems and produces class posterior probability estimates making it very useful for many real world applications. However, the training of KLR using gradient based methods or iterative re-weighted least squares can be unbearably slow for large datasets. Coupled with poor conditioning and parameter tuning, training KLR can quickly design matrix become infeasible for some real datasets. The goal of this paper is to present simple, fast, scalable, and efficient algorithms for learning KLR. First, based on a simple approximation of the logistic function, a least square algorithm for KLR is derived that avoids the iterative tuning of gradient based methods. Second, inspired by the extreme learning machine (ELM) theory, an explicit feature space is constructed through a generalized single hidden layer feedforward network and used for training iterative re-weighted least squares KLR (IRLS-KLR) and the newly proposed least squares KLR (LS-KLR). Finally, for large-scale and/or poorly conditioned problems, a robust and efficient preconditioned learning technique is proposed for learning the algorithms presented in the paper. Numerical results on a series of artificial and 12 real bench-mark datasets show first that LS-KLR compares favorable with SVM and traditional IRLS-KLR in terms of accuracy and learning speed. Second, the extension of ELM to KLR results in simple, scalable and very fast algorithms with comparable generalization performance to their original versions. Finally, the introduced preconditioned learning method can significantly increase the learning speed of IRLS-KLR.     

On the teaching and learing of Dienes' principles

Zoltan Dienes' principles of mathematical learning have been an integral part of mathematics education literature and applied both to the teaching and learning of mathematics as well as research on processes such as abstraction and generalization of mathematical structures. Most extant textbooks of cognitive learning theories in mathematics education include a treatment of Dienes' seminal contributions. Yet, there are no available studies at the tertiary level on how students internalise the meaning of Dienes' principles. This paper explores post-graduate mathematics education student's understanding of Dienes' principles and their ability to reflexively apply the principles to their own thinking on structurally similar problems. Some implications are offered for university educators engaged in the training of future researchers in the field.     

Implications for Developing and Researching Elementary School Mathematics Coaches

In recent years, national organizations, mathematics educators, and policy makers have called for the development of elementary school mathematics coaches to improve mathematics teaching and learning in elementary schools. The literacy field has found success and promise in the work of instructional coaches, and the mathematics education community can benefit from what professionals in literacy have learned and practiced. This article presents a synthesis of empirical research about instructional coaches, in both literacy and mathematics, as well as the neo‐Vygotskian construct of assisted performance. Following the synthesis, implications are presented regarding how to develop the essential skills and knowledge needed for elementary school mathematics coaches as well as how to examine the impact of their efforts in schools.     

On the behavior of ECN/RED gateways under a large number of TCP flows: Limit theorems

We consider a discrete-time stochastic model of an ECN/RED gateway where competing TCP sources share the link capacity. As the number of competing flows becomes large, the asymptotic queue behavior (normalized by the number of flows) at the gateway can be described by a simple recursion and the throughput behavior of individual TCP flows becomes asymptotically independent. A Central Limit Theorem complement is also presented, yielding a more accurate characterization of the asymptotic queue size. These results suggest a scalable yet accurate model of this complex large-scale stochastic feedback system, and crisply reveal the sources of queue fluctuations. This work was prepared through collaborative participation in the Communications and Networks Consortium sponsored by the U.S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-2-0011. This work was also supported by the Space and Naval Warfare Systems Center—San Diego under Contract No: N66001-00-C-8063. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government.     

Cooperative interval games: a survey

The (re)distribution of collective gains and costs is a central question for individuals and organizations contemplating cooperation under uncertainty. The theory of cooperative interval games provides a new game theoretical angle and suitable tools for answering this question. This survey aims to briefly present the state-of-the-art in this young field of research, discusses how the model of cooperative interval games extends the cooperative game theory literature, and reviews its existing and potential applications in economic and operations research situations with interval data.     

Using mixture‐amount modeling to optimize the advertising media mix and quantify cross‐media synergy for specific target groups

One of the critical decisions in media planning is how to allocate advertising efforts across different media. While studies indicate that marketers can create positive synergy effects by spreading their effort across several media, there is little understanding of how much should be invested in each specific medium to optimize advertising results. In this study, we apply a novel methodology, mixture‐amount modeling, which allows advertisers to determine the optimal allocation of advertising effort across media as a function of the total advertising effort. Moreover, we test how the optimal allocation and the resulting response change for consumers with distinctive media usage patterns and varying degrees of product category experience. Based on these results, we quantify the potential synergy between media and calculate the synergistic capacity for specific target groups. We apply the model to data from 52 beauty care advertising campaigns that ran on TV and in magazines in the Netherlands and Belgium. We determine the optimal allocation of advertising investments (measured through Gross Rating Points) to maximize campaign recognition. Our findings support the existence of positive synergistic effects between magazine and TV advertising and illustrate that these effects depend on consumers' media usage and product category experience.     

Newton's method for a class of nonsmooth functions

This paper presents and justifies a Newton iterative process for finding zeros of functions admitting a certain type of approximation. This class includes smooth functions as well as nonsmooth reformulations of variational inequalities. We prove for this method an analogue of the fundamental local convergence theorem of Kantorovich including optimal error bounds.The research reported here was sponsored by the National Science Foundation under Grants CCR-8801489 and CCR-9109345, by the Air Force Systems Command, USAF, under Grants AFOSR-88-0090 and F49620-93-1-0068, by the U. S. Army Research Office under Grant No. DAAL03-92-G-0408, and by the U. S. Army Space and Strategic Defense Command under Contract No. DASG60-91-C-0144. The U. S. Government has certain rights in this material, and is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon.     

Private Games are too Dangerous

Given the difficulty of observing interpersonal relations as they develop within an organization, I use iterated prisoner&2018;s dilemma games to simulate their development. The goal is to understand how trust could develop as a function of private games, that is, as a function of interaction sequences between two people independent of their relationships with other people. My baseline is Axelrod&2018;s results with TIT for TAT showing that cooperation can emerge as the dominant form of interaction even in a society of selfish individuals without central authority. I replicate Axelrod&2018;s results, then show that the results only occur in a rare social context&2014;maximum density networks. Where people form less dense networks by withdrawing from unproductive relationships, as is typical in organizations, the competitive advantage shifts from TIT for TAT to abusive strategies. A devious PUSHY strategy wins in moderate to high density networks. A blatantly HOSTILE strategy wins in less dense networks. Abusive players do well in sparse networks because their abuse is lucrative in the initial exchanges of a relationship&2014;before the other person knows to withdraw. Wise players avoiding the abusive players leaves the abusive players free to concentrate on naive players (con men thrive in big cities). The implication is that what keeps abusive players at bay are friends and acquaintances warning managers away from people known to exploit their colleagues. I reinforce the point with illustrative survey data to conclude that private games are not only too dangerous, but also too rare and too slow to be the foundation for trust within organizations. The results are an evidential call for the sociological intuition that trust and distrust cannot be understood independent of the network context in which they are produced.     

A dynamic solution concept for abstract games

Several solution concepts have been defined for abstract games. Some of these are the core, due to Gillies and Shapley, the Von Neumann-Morgenstern stable sets, and the subsolutions due to Roth. These solution concepts are rather static in nature. In this paper, we propose a new solution concept for abstract games, called the dynamic solution, that reflects the dynamic aspects of negotiation among the players. Some properties of the dynamic solution are studied. Also, the dynamic solution of abstract games arising fromn-person cooperative games in characteristic function form is investigated.This research was supported by the Office of Naval Research under Contract No. N00014-75-C-0678, by the National Science Foundation under Grants Nos. MPS-75-02024 and MCS-77-03984 at Cornell University, by the United States Army under Contract No. DAAG-29-75-C-0024, and by the National Science Foundation under Grant No. MCS-75-17385-A01 at the University of Wisconsin. The author is grateful to Professor W. F. Lucas under whose guidance the research was conducted.     

Landscapes of Investigation

According to many observations, traditional mathematics education falls within the exercise paradigm. This paradigm is contrasted with landscapes of investigation serving as invitations for students to be involved in processes of exploration and explanation. The distinction between the exercise paradigm and landscapes of investigation is combined with a distinction between three different types of reference which might provide mathematical concepts and classroom activities with meaning: references to mathematics; references to a semi-reality, and references to a real-life situation. The six possible learning milieus are illustrated by examples. Moving away from the exercise paradigm and in the direction of landscapes of investigation may help to abandon the authorities of the traditional mathematics classroom and to make students the acting subjects in their learning processes. Moving away from reference to pure mathematics and in the direction of real life references may help to provide resources for reflection on mathematics and its applications. My hope is that finding a route among the different milieus of learning may provide new resources for making the students both acting and reflecting and in this way providing mathematics education with a critical dimension.     

Simulation methods for queues: An overview

This paper gives an overview of those aspects of simulation methodology that are (to some extent) peculiar to the simulation of queueing systems. A generalized semi-Markov process framework for describing queueing systems is used through much of the paper. The main topics covered are: output analysis for simulation of transient and steady-state quantities, variance reduction methods that exploit queueing structure, and gradient estimation methods for performance parameters associated with queueing networks.The research of this author was supported by the U.S. Army Research Office under Contract DAAG29-84-K-0030.The research of this author was supported by the U.S. Army Research Office under Contract DAAG29-84-K-0030 and National Science Foundation Grant DCR-85-09668.