Cognition-Enhanced Machine Learning for Better Predictions with Limited Data.

The fields of machine learning (ML) and cognitive science have developed complementary approaches to computationally modeling human behavior. ML's primary concern is maximizing prediction accuracy; cognitive science's primary concern is explaining the underlying mechanisms. Cross-talk between these disciplines is limited, likely because the tasks and goals usually differ.

Personalized Training Schedules for Retention and Sustainment of Cardiopulmonary Resuscitation Skills.

Introduction: The study examined how the spacing of training during initial acquisition of cardiopulmonary resuscitation (CPR) skill affects longer-term retention and sustainment of these skills.

Methods: This was a multiphased, longitudinal study. Nursing students were randomly assigned to 2 initial acquisition conditions in which they completed 4 consecutive CPR training sessions spaced by shorter (1 or 7 days) or longer (30 or 90 days) training intervals.

Baseline Cardiopulmonary Resuscitation Skill Performance of Nursing Students Is Improved After One Resuscitation Quality Improvement Skill Refresher.

This article reports the results of baseline cardiopulmonary resuscitation (CPR) skills performance measurements from 467 nursing students. All participants had completed a CPR course. Baseline measurements were compared to performance after one 10-minute refresher training session on the Resuscitation Quality Improvement system.

Training interval in cardiopulmonary resuscitation.

Aim: Although evidence supports brief, frequent CPR training, optimal training intervals have not been established. The purpose of this study was to compare nursing students' CPR skills (compressions and ventilations) with 4 different spaced training intervals: daily, weekly, monthly, and quarterly, each for 4 times in a row.

Methods: Participants were nursing students (n = 475) in the first year of their prelicensure program in 10 schools of nursing across the United States.

Mechanisms underlying the spacing effect in learning: A comparison of three computational models.

The spacing effect is one of the most widely replicated results in experimental psychology: Separating practice repetitions by a delay slows learning but enhances retention. The current study tested the suitability of the underlying, explanatory mechanism in three computational models of the spacing effect. The relearning of forgotten material was measured, as the models differ in their predictions of how the initial study conditions should affect relearning.

Evaluating the Theoretic Adequacy and Applied Potential of Computational Models of the Spacing Effect.

The spacing effect is among the most widely replicated empirical phenomena in the learning sciences, and its relevance to education and training is readily apparent. Yet successful applications of spacing effect research to education and training is rare. Computational modeling can provide the crucial link between a century of accumulated experimental data on the spacing effect and the emerging interest in using that research to enable adaptive instruction.

The Model Human Processor and the older adult: parameter estimation and validation within a mobile phone task.

The authors estimate weighted mean values for nine information processing parameters for older adults using the Card, Moran, and Newell (1983) Model Human Processor model. The authors validate a subset of these parameters by modeling two mobile phone tasks using two different phones and comparing model predictions to a sample of younger (N = 20; M-sub(age) = 20) and older (N = 20; M-sub(age) = 69) adults. Older adult models fit keystroke-level performance at the aggregate grain of analysis extremely well (R = 0.

Expertise and age effects on knowledge activation in chess.

Novice, intermediate, and expert chess players of various ages, playing with two chess pieces on a quarter-section of a chessboard, performed a simple task to detect that the king is in check or is threatened with being in check. Age slowed response for both tasks. An interaction of task and skill revealed differences in diminishing response time between check and threat tasks as skill increased; experts were equally fast on both tasks.

Light pen use and practice minimize age and hand performance differences in pointing tasks.

We contrasted performance with mouse and light pen input devices for younger, middle-aged, and older adults (N = 72) who were experienced mouse users. Participants used both preferred and nonpreferred hands to perform a menu target selection task. The light pen minimized age differences in performance relative to the mouse.