Machine behaviourism: future visions of ‘learnification’ and ‘datafication’ across humans and digital technologies

ABSTRACT

This paper examines visions of ‘learning’ across humans and machines in a near-future of intensive data analytics. Building upon the concept of ‘learnification’, practices of ‘learning’ in emerging big data-driven environments are discussed in two significant ways: the training of machines, and the nudging of human decisions through digital choice architectures. Firstly, ‘machine learning’ is discussed as an important example of how data-driven technologies are beginning to influence educational activity, both through sophisticated technical expertise and a grounding in behavioural psychology. Secondly, we explore how educational software design informed by behavioural economics is increasingly intended to frame learner choices to influence and ‘nudge’ decisions towards optimal outcomes. Through the growing influence of ‘data science’ on education, behaviourist psychology is increasingly and powerfully invested in future educational practices. Finally, it is argued that future education may tend toward very specific forms of behavioural governance – a ‘machine behaviourism’ – entailing combinations of radical behaviourist theories and machine learning systems, that appear to work against notions of student autonomy and participation, seeking to intervene in educational conduct and shaping learner behaviour towards predefined aims.     

Administering Spatial and Cognitive Instruments In-class and On-line: Are These Equivalent?

Standardized, well-established paper-and-pencil tests, which measure spatial abilities or which measure reasoning abilities, have long been found to be predictive of success in the STEM (science, technology, engineering, and mathematics) fields. Instructors can use these tests for prediction of success and to inform instruction. A comparative administration of spatial visualization and cognitive reasoning tests, between in-class (proctored paper and pencil) and on-line (unproctored Internet) (N = 457), was used to investigate and to determine whether the differing instrument formats yielded equal measures of spatial ability and reasoning ability in large first-semester general chemistry sections. Although some gender differences were found, findings suggest that some differences across administration formats, but that on-line administration had similar properties of predicting chemistry performance as the in-class version. Therefore, on-line administration is a viable option for instructors to consider especially when dealing with large classes.     

SodaConstructing knowledge through exploratoids

In this article, we describe a preliminary study that integrates research on engineering design activities for K‐12 students with work on microworlds as learning tools. Here, we extend these bodies of research by exploring whether—and how—authentic recreations of engineering practices can help students develop conceptual understanding of physics. We focus on the design–build–test (DBT) cycle used by professional engineers in simulation‐based rapid modeling. In this experiment, middle‐school students worked for 10 hr during a single weekend to solve engineering design challenges using SodaConstructor, a Java‐based microworld, as a simulation environment. As a result of the experiment, students learned about center of mass. Our data further suggest that in the process of simulation‐based modeling, rapid iterations of the DBT cycle progressively linked students' interest in the design activities and understanding of the concept of center of mass. We suggest that these rapid iterations of the DBT cycle functioned as exploratoids: short fragments of exploratory action in a microworld that cumulatively develop interest in and understanding of important scientific concepts. © 2006 Wiley Periodicals, Inc. J Res Sci Teach     

Beyond the Total Score: A Preliminary Investigation into the Types of Phonological Awareness Errors Made by First Graders

Current phonological awareness assessment procedures consider only the total score a child achieves. Such an approach may result in children who achieve the same total score receiving the same instruction even though the configuration of their errors represent fundamental knowledge differences. The purpose of this study was to develop a tool for phonological awareness error classification and explore the types of errors made by 215 grade one children from low socioeconomic backgrounds on a phonological awareness test. Twenty-one distinct errors were identified and classified into eight categories. The most frequently occurring error category was Additions followed by Segmentations, Substitutions, Insertions, Repetitions, Omissions, Reversals, and Multiple Errors. Examination of a subsample of study participants who were classified as high and low reading performers revealed differences in the both the degree and type of errors exhibited. Low reading performers exhibited significantly more Insertion, Omission, Segmentation, and Substitution errors. Knowledge of child errors has the potential to enhance understanding and interpretation of child test performance and subsequent instructional recommendations.     

The ecological treatment of hyperkinesis

A model of hyperkinesis is introduced based on an ecological conception. The antecedents of hyperkinetic behavior are provided by a child's family environment, academic environment, and physiologic environment. These factors influence cognitive processes of the child. The consequences of hyperkinetic behavior often are undesirable, and so professional treatment is sought. Based on the ecological approach, effective treatment is multimodal and can involve the child, the family, and the school. No single approach to treatment is effective with all children.     

Clinical judgment vs. the computer: Can the school psychologist be replaced by a machine?

Can the school psychologist be replaced by a computer? The role of the computer in administering, scoring, and interpreting psychoeducational tests is examined. Both the intelligent computer model and the computer-as-assistant model are analyzed to determine what threat they may pose to the job security of school psychologists.