A novel technology for investigating the dynamics of infant perseverative reaching

We designed and tested a novel technology that enables us to capture the entire stream of behavior in perseverative reaching tasks. Beyond fitting the criteria of the conventional A-not-B task, the novel technology gives us better access to the core features of perseverative reaching, such as timing, behavior history, and reinforcement. The technology allows us to quantitatively manipulate reinforcement characteristics, to accurately program onsets, delays, and stimulus durations as well as locations and salience of the targets, and to automatically record the number of reaches to each target and compute timing. We did a validation study on this new technology, investigating the influence of a number of novel factors on perseverative reaching. We replicated the A-not-B phenomenon and associated developmental changes. In addition, results demonstrated that the new technology offers insights into infants' behavior beyond the first reaching action. Moreover, data collection is fully automated, yielding precise, quantitative data. Future studies using this technology will capitalize on the salient advantages of this technology to more precisely measure goal-directed actions and understand the development of reaching skill.     

COR V2: teaching observational research with multimedia courseware.

Courseware for Observational Research (COR Version 2) is an interactive multimedia program designed to teach the foundation of the scientific method: systematic observation. COR uses digital video with interactive coding to teach basic concepts, such as creating precise operational definitions; using frequency, interval, and duration coding; developing sampling strategies; and analyzing and interpreting data. Through lessons, a case study, and laboratory exercises, it gradually scaffolds students from teacher-directed learning into self-directed learning. The newest addition to COR is a case study in which students work collaboratively, using their own observations to make recommendations about a child's disruptive behavior in an after-school program. Evaluations of the lessons showed that classes using COR received better grades on their field observations than did those using methods that are more traditional. Students' confidence and knowledge increased as they moved through each section of the program.     

Patient inquiry into mental hospitalization: a quantitative analysis.

In this section we have assembled a small collection of data concerned with the issue of whether or not adolescents would profit from reflective inquiry into the closed area of mental health care. We have analyzed, arranged and interpreted the data from our study and conclude it demonstrates that adolescent inpatients did profit substantially from a reflective inquiry into mental health care. The number of subjects involved in this experimental program was small. The subjects of the experimental program were not selected randomly. Moreover, the researcher could not control for a number of intervening variables. For this particular group the intervening variables were many: changes in the subjects' individual treatment program, level of tranquilizing medication, attitude of other staff toward the experimental program, relations with parents or relatives, et cetera. This list covers some of the more important weaknesses of the experimental design. In the account of the experiment we reported the influence of other significant intervening variables as they emerged during the course of the study. Even with these important limitations the total push of the results in the direction of our argument compels us to conclude that it is clearly profitable for adolescent inpatients to reflectively inquire into the closed area of mental health care. Although the data reported here are not of predictive value, we believe they indicate the importance of having adolescent inpatients reflectively examine their social situation.     

COR V2: Teaching observational research with multimedia courseware

Courseware for Observational Research (COR Version 2) is an interactive multimedia program designed to teach the foundation of the scientific method: systematic observation. COR uses digital video with interactive coding to teach basic concepts, such as creating precise operational definitions; using frequency, interval, and duration coding; developing sampling strategies; and analyzing and interpreting data. Through lessons, a case study, and laboratory exercises, it gradually scaffolds students from teacher-directed learning into self-directed learning. The newest addition to COR is a case study in which students work collaboratively, using their own observations to make recommendations about a child’s disruptive behavior in an after-school program. Evaluations of the lessons showed that classes using COR received better grades on their field observations than did those using methods that are more traditional. Students’ confidence and knowledge increased as they moved through each section of the program.     

Structural equation modeling: reviewing the basics and moving forward

This tutorial begins with an overview of structural equation modeling (SEM) that includes the purpose and goals of the statistical analysis as well as terminology unique to this technique. I will focus on confirmatory factor analysis (CFA), a special type of SEM. After a general introduction, CFA is differentiated from exploratory factor analysis (EFA), and the advantages of CFA techniques are discussed. Following a brief overview, the process of modeling will be discussed and illustrated with an example using data from a HIV risk behavior evaluation of homeless adults (Stein & Nyamathi, 2000). Techniques for analysis of nonnormally distributed data as well as strategies for model modification are shown. The empirical example examines the structure of drug and alcohol use problem scales. Although these scales are not specific personality constructs, the concepts illustrated in this article directly correspond to those found when analyzing personality scales and inventories. Computer program syntax and output for the empirical example from a popular SEM program (EQS 6.1; Bentler, 2001) are included.     

Additive similarity trees

Similarity data can be represented by additive trees. In this model, objects are represented by the external nodes of a tree, and the dissimilarity between objects is the length of the path joining them. The additive tree is less restrictive than the ultrametric tree, commonly known as the hierarchical clustering scheme. The two representations are characterized and compared. A computer program, ADDTREE, for the construction of additive trees is described and applied to several sets of data. A comparison of these results to the results of multidimensional scaling illustrates some empirical and theoretical advantages of tree representations over spatial representations of proximity data.We thank Nancy Henley and Vered Kraus for providing us with data, and Jan deLeeuw for calling our attention to relevant literature. The work of the first author was supported in part by the Psychology Unit of the Israel Defense Forces.     

A program for parsing mouse movements into component submovements

Most current movement control theories include the idea that movement toward a target can be broken into several submovements. The complexity of analyzing a movement into its constituent submovement structure and the additional complexity imposed by the problem of noise in the data and hand tremor seem to be daunting to researchers. This paper discusses a program that can ameliorate both of these problems and parse movements into their constituent submovements. It also contains a graphing feature that is useful as a visual tool for analyzing submovement structure. The programs are easily modifiable, so that researchers can specify their own parsing rules on the basis of different assumptions about movement control and use the parser for data from different experimental tasks.     

Effect of Platform Used for Data Collection on Open-Ended Response Quality

Although the validity of collecting quantitative data using electronic platforms has been widely accepted, there has been concern that qualitative data collected on an electronic platform may not provide the same depth and richness in response quality as data collected using the pen-and-paper format. This article compares the quality of responses to open-ended questions collected using the pen-and-paper platform with responses collected using an electronic platform. Data for a program evaluation study were collected using either the pen-and-paper platform, an iPad, or an iPad Mini at a series of after-hours events for adults at the Center of Science and Industry, a Midwest science center. Metrics were designed to calculate a comprehensive response score consisting of the breadth of information and the richness of detail in open-ended item responses, allowing us to compare the overall response quality between the three platforms. Results indicate that qualitative data collected using electronic devices are as broad and detailed as data collected using traditional pen-and-paper techniques.     

Exploratory longitudinal factor analysis in multiple populations

For multiple populatios, a longtidinal factor analytic model which is entirely exploratory, that is, no explicit identification constraints, is proposed. Factorial collapse and period/practice effects are allowed. An invariant and/or stationary factor pattern is permitted. This model is formulated stochastically. To implement this model a stagewise EM algorithm is developed. Finally a numerical illustration utilizing Nesselroade and Baltes' data is presented.The authors wish to thank Barbara Mellers and Henry Kaiser for their helpful comments and John Nesselroade for providing us the data for our illustration. This research wwa supported in part by a grant (No. AG03164) from the National Institute on Aging to William Meredith. Details of the derivations and a copy of the PROC MATRIX program are available upon request from the first author.     

A Developing Approach to Studying Students’ Learning through Their Mathematical Activity

We discuss an emerging program of research on a particular aspect of mathematics learning, students’ learning through their own mathematical activity as they engage in particular mathematical tasks. Prior research in mathematics education has characterized learning trajectories of students by specifying a series of conceptual steps through which students pass in the context of particular instructional approaches or learning environments. Generally missing from the literature is research that examines the process by which students progress from one of these conceptual steps to a subsequent one. We provide a conceptualization of a program of research designed to elucidate students’ learning processes and describe an emerging methodology for this work. We present data and analysis from an initial teaching experiment that illustrates the methodology and demonstrates the learning that can be fostered using the approach, the data that can be generated, and the analyses that can be done. The approach involves the use of a carefully designed sequence of mathematical tasks intended to promote particular activity that is expected to result in a new concept. Through analysis of students’ activity in the context of the task sequence, accounts of students’ learning processes are developed. Ultimately a large set of such accounts would allow for a cross-account analysis aimed at articulating mechanisms of learning.     

Family Sculpting in Preventive Work with "Well Families"

This paper will describe an experimental community project aimed at "well families". The program was designed to be preventive by providing service to families before their problems escalated into crisis proportions. It emphasized an educational rather than treatment bias; this orientation forced us to expand concepts, experiment with new techniques, and re-evaluate our ideas on how families change. Of particular importance to us was the emphasis on behavioral change rather than intellectual insight. In the course of this work, family sculpting came to be an increasingly valuable tool.     

ACACIA: an agent-based program for simulating behavior to reach long-term goals

We present ACACIA, an agent-based program implemented in Java StarLogo 2.0 that simulates a two-dimensional microworld populated by agents, obstacles and goals. Our program simulates how agents can reach long-term goals by following sensorial-motor couplings (SMCs) that control how the agents interact with their environment and other agents through a process of local categorization. Thus, while acting in accordance with this set of SMCs, the agents reach their goals through the emergence of global behaviors. This agent-based simulation program would allow us to understand some psychological processes such as planning behavior from the point of view that the complexity of these processes is the result of agent–environment interaction.     

Multiple Imputation for Multivariate Missing-Data Problems: A Data Analyst's Perspective

Analyses of multivariate data are frequently hampered by missing values. Until recently, the only missing-data methods available to most data analysts have been relatively ad1 hoc practices such as listwise deletion. Recent dramatic advances in theoretical and computational statistics, however, have produced anew generation of flexible procedures with a sound statistical basis. These procedures involve multiple imputation (Rubin, 1987), a simulation technique that replaces each missing datum with a set of m > 1 plausible values. The rn versions of the complete data are analyzed by standard complete-data methods, and the results are combined using simple rules to yield estimates, standard errors, and p-values that formally incorporate missing-data uncertainty. New computational algorithms and software described in a recent book (Schafer, 1997a) allow us to create proper multiple imputations in complex multivariate settings. This article reviews the key ideas of multiple imputation, discusses the software programs currently available, and demonstrates their use on data from the Adolescent Alcohol Prevention Trial (Hansen & Graham, 199 I).     

Missing: critical and skeptical perspectives on comprehensive soldier fitness

The author read with interest, and concern, the January 2011 issue of the American Psychologist. The Special Issue on Comprehensive Soldier Fitness addressed a hugely consequential national issue and offered a vision for psychological resilience along with an elaborate set of supporting articles, concluding with some comments on "Objections" to psychologists working with the military. While a bold vision was offered and a game plan presented, no data or evidence are yet available (it is far too early in the process), and that should concern us all. The author hopes the American Psychological Association (APA) and the American Psychologist offer skeptical and critical views in future issues on the issue of the psychological health of our military and as evidence emerges regarding the Comprehensive Soldier Fitness program.     

Is there a geometric module for spatial orientation? squaring theory and evidence

There is evidence, beginning with Cheng (1986), that mobile animals may use the geometry of surrounding areas to reorient following disorientation. Gallistel (1990) proposed that geometry is used to compute the major or minor axes of space and suggested that such information might form an encapsulated cognitive module. Research reviewed here, conducted on a wide variety of species since the initial discovery of the use of geometry and the formulation of the modularity claim, has supported some aspects of the approach, while casting doubt on others. Three possible processing models are presented that vary in the way in which (and the extent to which) they instantiate the modularity claim. The extant data do not permit us to discriminate among them. We propose a modified concept of modularity for which an empirical program of research is more tractable.     

Fibring Argumentation Frames

This paper is part of a research program centered around argumentation networks and offering several research directions for argumentation networks, with a view of using such networks for integrating logics and network reasoning. In Section 1 we introduce our program manifesto. In Section 2 we motivate and show how to substitute one argumentation network as a node in another argumentation network. Substitution is a purely logical operation and doing it for networks, besides developing their theory further, also helps us see how to bring logic and networks closer together. Section 3 develops the formal properties of the new kind of network and Section 4 offers general discussion and comparison with the literature.     

SIMPLIFYING HEURISTICS VERSUS CAREFUL THINKING: SCIENTIFIC ANALYSIS OF MILLENNIAL SPIRITUAL ISSUES

There is ample evidence that humans (and other primates) possess a knowledge instinct—a biologically driven impulse to make coherent sense of the world at the highest level possible. Yet behavioral decision‐making data suggest a contrary biological drive to minimize cognitive effort by solving problems using simplifying heuristics. Individuals differ, and the same person varies over time, in the strength of the knowledge instinct. Neuroimaging studies suggest which brain regions might mediate the balance between knowledge expansion and heuristic simplification. One region implicated in primary emotional experience is more activated in individuals who use primitive heuristics, whereas two areas of the cortex are more activated in individuals with a strong knowledge drive: one region implicated in detecting risk or conflict and another implicated in generating creative ideas. Knowledge maximization and effort minimization are both evolutionary adaptations, and both are valuable in different contexts. Effort minimization helps us make minor and routine decisions efficiently, whereas knowledge maximization connects us to the beautiful, to the sublime, and to our highest aspirations. We relate the opposition between the knowledge instinct and heuristics to the biblical story of the fall, and argue that the causal scientific worldview is mathematically equivalent to teleological arguments from final causes. Elements of a scientific program are formulated to address unresolved issues.     

A FORTRAN IV program for analyzing higher-order subjective organization units in free recall learning

This paper presents a program for the analysis of subjective organization in free recall and the instructions for the organization of data to use this program. The program is capable of handling lists of up to 40 items, as well as 20 trials of data. In addition, the program provides several types of data tables for unit sizes from 2 to 10 items in length and for three types of sequential ordering criteria.     

Ideal point discriminant analysis

A new method of multiple discriminant analysis was developed that allows a mixture of continuous and discrete predictors. The method can be justified under a wide class of distributional assumptions on the predictor variables. The method can also handle three different sampling situations, conditional, joint and separate. In this method both subjects (cases or any other sampling units) and criterion groups are represented as points in a multidimensional euclidean space. The probability of a particular subject belonging to a particular criterion group is stated as a decreasing function of the distance between the corresponding points. A maximum likelihood estimation procedure was developed and implemented in the form of a FORTRAN program. Detailed analyses of two real data sets were reported to demonstrate various advantages of the proposed method. These advantages mostly derive from model evaluation capabilities based on the Akaike Information Criterion (AIC).The work reported in this paper has been supported by Grant A6394 from the Natural Sciences and Engineering Research Council of Canada and by a leave grant from the Social Sciences and Humanities Research Council of Canada to the first author. Portions of this study were conducted while the first author was at the Institute of Statistical Mathematics in Tokyo on leave from McGill University. He would like to express his gratitude to members of the Institute for their hospitality. Thanks are also due to T. Komazawa at the Institute for letting us use his data, to W. J. Krzanowski at the University of Reading for providing us with Armitage, McPherson, and Copas' data, and to Don Ramirez, Jim Ramsay and Stan Sclove for their helpful comments on an earlier draft of this paper.