The effects of operator implementation cost on planfulness of problem solving and learning

Mutual interplay between cognitive offloading and secondary task performance

Various modern tools, such as smartphones, allow for cognitive offloading (i.e., the externalization of cognitive processes). In this study, we examined the use and consequences of cognitive offloading in demanding situations in which people perform multiple tasks concurrently-mimicking the requirements of daily life. In a preregistered study, we adapted the dual-task paradigm so that one of the tasks allowed for cognitive offloading. As a primary task, our participants (N = 172) performed the pattern copy task-a highly demanding working memory task that allows for offloading at various degrees. In this task, we manipulated the temporal costs of offloading. Concurrently, half of the participants responded to a secondary N-back task. As our main research question, we investigated the impact of offloading behavior on secondary task performance. We observed that more pronounced offloading in the condition without temporal costs was accompanied by a more accurate performance in the N-back task. Furthermore, the necessity to respond to the N-back task increased offloading behavior. These results suggest an interplay between offloading and secondary task performance: in demanding situations, individuals increasingly use cognitive offloading, which releases internal resources that can then be devoted to improving performance in other, concurrent tasks.

Supporting Cognition With Modern Technology: Distributed Cognition Today and in an AI-Enhanced Future

In the present article, we explore prospects for using artificial intelligence (AI) to distribute cognition via cognitive offloading (i.e., to delegate thinking tasks to AI-technologies). Modern technologies for cognitive support are rapidly developing and increasingly popular. Today, many individuals heavily rely on their smartphones or other technical gadgets to support their daily life but also their learning and work. For instance, smartphones are used to track and analyze changes in the environment, and to store and continually update relevant information. Thus, individuals can offload (i.e., externalize) information to their smartphones and refresh their knowledge by accessing it. This implies that using modern technologies such as AI empowers users via offloading and enables them to function as always-updated knowledge professionals, so that they can deploy their insights strategically instead of relying on outdated and memorized facts. This AI-supported offloading of cognitive processes also saves individuals' internal cognitive resources by distributing the task demands into their environment. In this article, we provide (1) an overview of empirical findings on cognitive offloading and (2) an outlook on how individuals' offloading behavior might change in an AI-enhanced future. More specifically, we first discuss determinants of offloading such as the design of technical tools and links to metacognition. Furthermore, we discuss benefits and risks of cognitive offloading. While offloading improves immediate task performance, it might also be a threat for users' cognitive abilities. Following this, we provide a perspective on whether individuals will make heavier use of AI-technologies for offloading in the future and how this might affect their cognition. On one hand, individuals might heavily rely on easily accessible AI-technologies which in return might diminish their internal cognition/learning. On the other hand, individuals might aim at enhancing their cognition so that they can keep up with AI-technologies and will not be replaced by them. Finally, we present own data and findings from the literature on the assumption that individuals' personality is a predictor of trust in AI. Trust in modern AI-technologies might be a strong determinant for wider appropriation and dependence on these technologies to distribute cognition and should thus be considered in an AI-enhanced future.

Impact of Intrinsic Cognitive Skills and Metacognitive Beliefs on Tool Use Performance

Cognitive tools (e.g., calculators) provide all users with the same potential. Yet when people use such cognitive tools, interindividual variations are observed. Previous findings have indicated that 2 main factors could explain these variations: intrinsic cognitive skills (i.e., the “non–tool use” cognitive skills associated with the task targeted) and metacognitive beliefs about one's performance with tool use. In this study we sought to reproduce these findings and to investigate in more detail the nature of the relationships (i.e., linear vs. exponential) between tool use performance and intrinsic cognitive skills. In Experiment 1, 200 participants completed 2 cognitive tasks (calculation and geography) in 2 conditions (non–tool use vs. tool use). In Experiment 2, 70 participants performed a geography task in 2 conditions (non–tool use vs. tool use) and estimated their performance in each condition before completing the task. Results indicated that intrinsic cognitive skills and, to a lesser extent, metacognitive beliefs improved tool use performance: The higher the intrinsic cognitive skills and the higher participants estimated their tool use performance, the higher this tool use performance was. The nature of the relationship between tool use performance and intrinsic cognitive skills appeared to be linear rather than exponential. These findings extend previous research showing a strong impact of intrinsic cognitive skills on the performance associated with the use of cognitive tools or external aids.

Attaining the recesses of the cognitive space

Existing neuropsychological tests of executive function often manifest a difficulty pinpointing cognitive deficits when these are intermittent and come in the form of omissions. We discuss the hypothesis that two partially interrelated reasons for this failure stem from relative inability of neuropsychological tests to explore the cognitive space and to explicitly take into account strategic and opportunistic resource allocation decisions, and to address the temporal aspects of both behaviour and task-related brain function in data analysis. Criteria for tasks suitable for neuropsychological assessment of executive function, as well as appropriate ways to analyse and interpret observed behavioural data are suggested. It is proposed that experimental tasks should be devised which emphasize typical rather than optimal performance, and that analyses should quantify path-dependent fluctuations in performance levels rather than averaged behaviour. Some implications for experimental neuropsychology are illustrated for the case of planning and problem-solving abilities and with particular reference to cognitive impairment in closed-head injury.

Individual differences in cognitive offloading: a comparison of intention offloading, pattern copy, and short-term memory capacity

The cognitive load of many everyday life tasks exceeds known limitations of short-term memory. One strategy to compensate for information overload is cognitive offloading which refers to the externalization of cognitive processes such as reminder setting instead of memorizing. There appears to be remarkable variance in offloading behavior between participants which poses the question whether there is a common factor influencing offloading behavior across different tasks tackling short-term memory processes. To pursue this question, we studied individual differences in offloading behavior between two well-established offloading paradigms: the intention offloading task which tackles memory for intentions and the pattern copy task which tackles continuous short-term memory load. Our study also included an unrelated task measuring short-term memory capacity. Each participant completed all tasks twice on two consecutive days in order to obtain reliability scores. Despite high reliability scores, individual differences in offloading behavior were uncorrelated between the two offloading tasks. In both tasks, however, individual differences in offloading behavior were correlated with the individual differences in an unrelated short-term memory task. Our results therefore show that offloading behavior cannot simply be explained in terms of a single common factor driving offloading behavior across tasks. We discuss the implications of this finding for future research investigating the interrelations of offloading behavior across different tasks.

Consequences of cognitive offloading: Boosting performance but diminishing memory

Modern technical tools such as tablets allow for the temporal externalisation of working memory processes (i.e., cognitive offloading). Although such externalisations support immediate performance on different tasks, little is known about potential long-term consequences of offloading behaviour. In the current set of experiments, we studied the relationship between cognitive offloading and subsequent memory for the offloaded information as well as the interplay of this relationship with the goal to acquire new memory representations. Our participants solved the Pattern Copy Task, in which we manipulated the costs of cognitive offloading and the awareness of a subsequent memory test. In Experiment 1 (N = 172), we showed that increasing the costs for offloading induces reduced offloading behaviour. This reduction in offloading came along with lower immediate task performance but more accurate memory in an unexpected test. In Experiment 2 (N = 172), we confirmed these findings and observed that offloading behaviour remained detrimental for subsequent memory performance when participants were aware of the upcoming memory test. Interestingly, Experiment 3 (N = 172) showed that cognitive offloading is not detrimental for long-term memory formation under all circumstances. Those participants who were forced to offload maximally but were aware of the memory test could almost completely counteract the negative impact of offloading on memory. Our experiments highlight the importance of the explicit goal to acquire new memory representations when relying on technical tools as offloading did have detrimental effects on memory without such a goal.

Latency Management in Scribble-Based Interactive Segmentation of Medical Images

OBJECTIVE

During an interactive image segmentation task, the outcome is strongly influenced by human factors. In particular, a reduction in computation time does not guarantee an improvement in the overall segmentation time. This paper characterizes user efficiency during scribble-based interactive segmentation as a function of computation time.

METHODS

We report a controlled experiment with users who experienced eight different levels of simulated latency (ranging from 100 to 2000 ms) with two techniques for refreshing visual feedback (either automatic, where the segmentation was recomputed and displayed continuously during label drawing, or user initiated, which was only computed and displayed each time the user hits a defined button).

RESULTS

For short latencies, the user's attention is focused on the automatic visual feedback, slowing down his/her labeling performance. This effect is attenuated as the latency grows larger, and the two refresh techniques yield similar user performance at the largest latencies. Moreover, during the segmentation task, participants spent in average for automatic refresh and for user-initiated refresh of the overall segmentation time interpreting the results.

CONCLUSION

The latency is perceived differently according to the refresh method used during the segmentation task. Therefore, it is possible to reduce its impact on the user performance.

SIGNIFICANCE

This is the first time a study investigates the effects of latency in an interactive segmentation task. The analysis and recommendations provided in this paper help understanding the cognitive mechanisms in interactive image segmentation.

Predicting Short-Term Remembering as Boundedly Optimal Strategy Choice

It is known that, on average, people adapt their choice of memory strategy to the subjective utility of interaction. What is not known is whether an individual's choices are boundedly optimal. Two experiments are reported that test the hypothesis that an individual's decisions about the distribution of remembering between internal and external resources are boundedly optimal where optimality is defined relative to experience, cognitive constraints, and reward. The theory makes predictions that are tested against data, not fitted to it. The experiments use a no-choice/choice utility learning paradigm where the no-choice phase is used to elicit a profile of each participant's performance across the strategy space and the choice phase is used to test predicted choices within this space. They show that the majority of individuals select strategies that are boundedly optimal. Further, individual differences in what people choose to do are successfully predicted by the analysis. Two issues are discussed: (a) the performance of the minority of participants who did not find boundedly optimal adaptations, and (b) the possibility that individuals anticipate what, with practice, will become a bounded optimal strategy, rather than what is boundedly optimal during training.

Learning and interactivity in solving a transformation problem

Outside the psychologist's laboratory, thinking proceeds on the basis of a great deal of interaction with artefacts that are recruited to augment problem-solving skills. The role of interactivity in problem solving was investigated using a river-crossing problem. In Experiment 1A, participants completed the same problem twice, once in a low interactivity condition, and once in a high interactivity condition (with order counterbalanced across participants). Learning, as gauged in terms of latency to completion, was much more pronounced when the high interactivity condition was experienced second. When participants first completed the task in the high interactivity condition, transfer to the low interactivity condition during the second attempt was limited; Experiment 1B replicated this pattern of results. Participants thus showed greater facility to transfer their experience of completing the problem from a low to a high interactivity condition. Experiment 2 was designed to determine the amount of learning in a low and high interactivity condition; in this experiment participants completed the problem twice, but level of interactivity was manipulated between subjects. Learning was evident in both the low and high interactivity groups, but latency per move was significantly faster in the high interactivity group, in both presentations. So-called problem isomorphs instantiated in different task ecologies draw upon different skills and abilities; a distributed cognition analysis may provide a fruitful perspective on learning and transfer.

The Effects of Interactive Latency on Exploratory Visual Analysis

To support effective exploration, it is often stated that interactive visualizations should provide rapid response times. However, the effects of interactive latency on the process and outcomes of exploratory visual analysis have not been systematically studied. We present an experiment measuring user behavior and knowledge discovery with interactive visualizations under varying latency conditions. We observe that an additional delay of 500 ms incurs significant costs, decreasing user activity and data set coverage. Analyzing verbal data from think-aloud protocols, we find that increased latency reduces the rate at which users make observations, draw generalizations and generate hypotheses. Moreover, we note interaction effects in which initial exposure to higher latencies leads to subsequently reduced performance in a low-latency setting. Overall, increased latency causes users to shift exploration strategy, in turn affecting performance. We discuss how these results can inform the design of interactive analysis tools.

Act first, think later: the presence and absence of inferential planning in problem solving

Planning is fundamental to successful problem solving, yet individuals sometimes fail to plan even one step ahead when it lies within their competence to do so. In this article, we report two experiments in which we explored variants of a ball-weighing puzzle, a problem that has only two steps, yet nonetheless yields performance consistent with a failure to plan. The results fit a computational model in which a solver's attempts are determined by two heuristics: maximization of the apparent progress made toward the problem goal and minimization of the problem space in which attempts are sought. The effectiveness of these heuristics was determined by lookahead, defined operationally as the number of steps evaluated in a planned move. Where move outcomes cannot be visualized but must be inferred, planning is constrained to the point where some individuals apply zero lookahead, which with n-ball problems yields seemingly irrational unequal weighs. Applying general-purpose heuristics with or without lookahead accounts for a range of rational and irrational phenomena found with insight and noninsight problems.

Balancing energetic and cognitive resources: memory use during search depends on the orienting effector

Search outside the laboratory involves tradeoffs among a variety of internal and external exploratory processes. Here we examine the conditions under which item specific memory from prior exposures to a search array is used to guide attention during search. We extend the hypothesis that memory use increases as perceptual search becomes more difficult by turning to an ecologically important type of search difficulty - energetic cost. Using optical motion tracking, we introduce a novel head-contingent display system, which enables the direct comparison of search using head movements and search using eye movements. Consistent with the increased energetic cost of turning the head to orient attention, we discover greater use of memory in head-contingent versus eye-contingent search, as reflected in both timing and orienting metrics. Our results extend theories of memory use in search to encompass embodied factors, and highlight the importance of accounting for the costs and constraints of the specific motor groups used in a given task when evaluating cognitive effects.

Physically distributed learning: adapting and reinterpreting physical environments in the development of fraction concepts

Five studies examined how interacting with the physical environment can support the development of fraction concepts. Nine- and 10-year-old children worked on fraction problems they could not complete mentally. Experiments 1 and 2 showed that manipulating physical pieces facilitated children's ability to develop an interpretation of fractions. Experiment 3 demonstrated that when children understood a content area well, they used their interpretations to repurpose many environments to support problem solving, whereas when they needed to learn, they were prone to the structure of the environment. Experiments 4 and 5 examined transfer after children had learned by manipulating physical pieces. Children who learned by adapting relatively unstructured environments transferred to new materials better than children who learned with "well-structured" environments that did not require equivalent adaptation. Together, the findings reveal that during physically distributed learning, the opportunity to adapt an environment permits the development of new interpretations that can advance learning.

Paying the price works: increasing goal-state access cost improves problem solving and mitigates the effect of interruption

The aim of this paper was to investigate whether it was possible to induce more internal planning in the four-disk Tower of Hanoi (ToH) in order not only to produce more efficient problem solving but also to make it more resistant to the negative effect of interruption. The theoretical frameworks of soft constraints and the memory for goals model underpinned Experiments 1 and 2. In both experiments, three goal-state access cost conditions were used: high (mouse movements and 2.5-s delay), medium (mouse movements) and low (goal state always available). In Experiment 1, more memory-based planning was induced by the high cost condition, which resulted in fewer moves to solution and the gradual development of an efficient subgoaling strategy, resulting in more perfect solutions. In Experiment 2, the same condition protected performance against a 10-s interruption irrespective of the interrupting task (blank screen, mental arithmetic, or three-disk ToH). The more memory-based planning strategy, induced by high access cost, presumably strengthened participants' goals during planning and problem solving, making them less susceptible to decay and interference from interruption. These novel results are discussed in the context of other recent studies.

Understanding age and technology experience differences in use of prior knowledge for everyday technology interactions

Technology designers must understand relevant prior knowledge in a target user population to facilitate adoption and effective use. To assess prior knowledge used in naturalistic settings, we systematically collected information about technologies used over 10-day periods from older adults with high and low technology experience and younger adults. Technology repertoires for younger adults and high technology older adults were similar; differences reflected typically different needs for kitchen and health care technologies between the age groups. Technology repertoires for low-technology older adults showed substantial technology usage in many categories. Lower usage compared to high-tech older adults for each category was limited primarily to PC and Internet technologies. Experience differences suggest preferences among low-technology older adults for basic technology usage and for working with people rather than technologies.

Participants in all groups were generally successful using their everyday technologies to achieve their goals. Prior knowledge was the most common attribution for success, but external information was also commonly referenced. Relevant prior knowledge included technical, functional, strategy, and self knowledge. High tech older adults did not report more problems than younger adults, but they did attribute more problems to insufficient prior knowledge. Younger adults attributed more problems to interference from prior knowledge. Low-tech older adults reported fewer problems, typically attributing them to insufficient prior knowledge or product/system faults. We discuss implications for further research and design improvements to increase everyday technology success and adoption for high-tech and low-tech older adults.

The influence of goal-state access cost on planning during problem solving

Two problem-solving experiments investigated the relationship between planning and the cost of accessing goal-state information using the theoretical framework of the soft constraints hypothesis (Gray & Fu, 2004; Gray, Simms, Fu, & Schoelles, 2006). In Experiment 1, 36 participants were allocated to low, medium, and high access cost conditions and completed a problem-solving version of the Blocks World Task. Both the nature of planning (memory based or display based) and its timing (before or during action) changed with high goal-state access cost (a mouse movement and a 2.5-s delay). In this condition more planning before action was observed, with less planning during action, evidenced by longer first-move latencies, more moves per goal-state inspection, and more short (≤ 0.8 s) and long (>8 s) "preplanned" intermove latencies. Experiment 2 used an eight-puzzle-like transformation task and replicated the effect of goal-state access cost when more complex planning was required, also confirmed by sampled protocol data. Planning before an episode of move making increased with higher goal-state access cost, and planning whilst making moves increased with lower access cost. These novel results are discussed in the context of the soft constraints hypothesis.

The strategic nature of changing your mind

In two experiments, we studied how people's strategy choices emerge through an initial and then a more considered evaluation of available strategies. The experiments employed a computer-based paradigm where participants solved multiplication problems using mental and calculator solutions. In addition to recording responses and solution times, we gathered data on mouse cursor movements. Participants' motor behavior was revealing; although people rapidly initiated movement to the calculator box or the answer input box, they frequently changed their minds and went to the other box. Movement initiation direction depended on problem difficulty and calculator responsiveness. Ultimate strategy selection also depended on these factors, but was further influenced by movement initiation direction. We conclude that strategy selection is iterative, as revealed by these differences between early cursor movement and eventual strategy implementation. After rapidly initiating movement favoring one strategy, people carefully evaluate the applicability of that strategy in the current context.

The soft constraints hypothesis: a rational analysis approach to resource allocation for interactive behavior

Soft constraints hypothesis (SCH) is a rational analysis approach that holds that the mixture of perceptual-motor and cognitive resources allocated for interactive behavior is adjusted based on temporal cost-benefit tradeoffs. Alternative approaches maintain that cognitive resources are in some sense protected or conserved in that greater amounts of perceptual-motor effort will be expended to conserve lesser amounts of cognitive effort. One alternative, the minimum memory hypothesis (MMH), holds that people favor strategies that minimize the use of memory. SCH is compared with MMH across 3 experiments and with predictions of an Ideal Performer Model that uses ACT-R's memory system in a reinforcement learning approach that maximizes expected utility by minimizing time. Model and data support the SCH view of resource allocation; at the under 1000-ms level of analysis, mixtures of cognitive and perceptual-motor resources are adjusted based on their cost-benefit tradeoffs for interactive behavior.

Solving combinatorial problems: the 15-puzzle

We present a series of experiments in which human subjects were tested with a well-known combinatorial problem called the 15-puzzle and in different-sized variants of this puzzle. Subjects can solve these puzzles reliably by systematically building a solution path, without performing much search and without using distances among the states of the problem. The computational complexity of the underlying mental mechanisms is very low. We formulated a computational model of the underlying cognitive processes on the basis of our results. This model applied a pyramid algorithm to individual stages of each problem. The model's performance proved to be quite similar to the subjects' performance.

Lasting reductions in illegal moves following an increase in their cost: evidence from river-crossing problems

The authors present 3 experiments demonstrating ways to reduce illegal moves in problem-solving tasks. They propose a 3-stage framework for the rejection of illegal moves. An illegal move must come to mind and be selected, checked for legality, and correctly rejected. Illegal move reduction can occur at any stage. Control group participants benefited from solving the same problem twice but failed to show transfer to an isomorph, replicating results from S. K. Reed, G. W. Ernst, and R. Banerji (1974). Participants who were penalized for making illegal moves showed reductions in illegal moves even when solving a novel isomorph without penalty. The authors propose that illegal move reduction occurs when solvers are cautious and check moves for legality frequently.

Initial and concurrent planning in solutions to well-structured problems

Two experiments are reported, which consider planning behaviour in the context of a well-structured problem. One question in the problem-solving literature is to what extent planning a solution to a problem takes place before attempting that problem and whether this takes precedence over planning while solving a problem, hereafter referred to as concurrent planning. An additional question is whether the adoption of one mode of planning confers a performance advantage and under what circumstances one strategy is adopted in preference to others. The studies reported here set out to investigate the effects on performance of adopting different modes of planning and whether there is any relationship between the adoption of different strategic approaches and problem-solving performance. The results of these studies suggest that initial planning can enhance problem-solving performance, but only when problems remain relatively simple. As problem complexity increases the effects of initial planning appear to have little or no effect upon performance. In conclusion it is suggested that strategy use depends upon the interactions between individual preference for a given strategy, problem complexity, and the stage that one has reached in the development of a solution to a problem.

Performance in Planning: Processes, Requirements, and Errors

Planning is not only an aspect of our day-to-day lives, it represents a critical aspect of performance on many high-level tasks. Although few of us would dispute the need for planning, the psychology of planning remains relatively undeveloped. With this point in mind, the intent in the present article was to review the available literature on planning. The authors begin by examining alternative models of planning and delineating their implications for performance. Subsequently, the findings obtained in various studies of planning are reviewed with respect to 8 key questions ranging from when planning is useful to how errors in planning should be minimized. The implications of current answers to these questions are discussed in terms of research needs and development of a more comprehensive theoretical understanding of performance in planning.

Move evaluation as a predictor and moderator of success in solutions to well-structured problems

This paper presents three studies concerned with the evaluation of moves in solutions to Tower of Hanoi problems and the effect that such evaluation processes have on solution success. The existing literature on problem solving suggests that verbalizing whilst solving a problem can have a positive effect upon performance. However, such verbalization has to be directed toward an explicit evaluation of particular moves. What remains unclear is whether evaluation without verbalization has the same effects or whether some characteristic of the process of verbalization gives rise to improved performance on such tasks. For example, the act of verbalizing per se may simply mean that more processing time is directed toward the problem-solving process. The studies reported in this paper suggest that the process of evaluation may be independent of verbalization processes and that non-verbal evaluation of moves (indicated by a key press) produces the same effects as a verbal evaluation of such moves. Moreover, the process of evaluating moves appears to produce a form of behaviour that is prone to disruption via the administration of secondary tasks, whereas non-evaluated solutions are not. This may suggest that problem solvers who engage in evaluation processes develop an explicit representation of the strategies used to solve the problem.