The goal specificity effect on strategy use and instructional efficiency during computer-based scientific discovery learning

Using a computer-based scientific discovery learning environment on buoyancy in fluids we investigated the effects of goal specificity (nonspecific goals vs. specific goals) for two goal types (problem solving goals vs. learning goals) on strategy use and instructional efficiency. Our empirical findings close an important research gap, because in earlier studies the goal specificity effect either was restricted to one goal type or goal type was confounded with goal specificity. In addition, there is hardly a study with empirical evidence for the goal specificity effect on strategy use, which counts even more for a cognitive cost-benefit ratio as a dependent variable. Instead, in earlier studies the goal specificity effect has been attributed to differences in strategy use and cognitive cost-benefit ratio in a rather theoretical way. In the present study for strategy use an interaction was found between goal specificity and goal type, indicating that the goal specificity effect occurs only in case of problem solving goals, but not in case of learning goals. Compared to students provided with specific problem solving goals, students who worked on nonspecific problem solving goals, used a control of variables-strategy more frequently. Additionally, we found a main effect of goal specificity on instructional efficiency for both of the goal types, pointing at a more favorable relationship between performance gain and cognitive load caused by nonspecific goals.     

The interplay between cognitive and motivational variables in a supportive online learning system for secondary physical education

A path model was used to test the unique and interactive effects of cognitive and motivational variables when learning in a supportive online learning system, Collaborative Inquiry System (CIS). In this student-centered learning environment, students interact with computer simulations and are assisted by online scaffolds intended to help them learn complex scientific concepts. The present study also explored the relationships between students’ motivational, cognitive, and metacognitive strategy use and online performance. In total, 178 tenth-grade students participated in the study. The statistical analyses revealed that students’ learning goals and cognitive preferences predicted metacognitive strategy use and later influenced their performance. Prior knowledge is a predictor of neither metacognitive strategy use nor learning goals and need for cognition, but is nevertheless an important determinant of online performance. Discussions on how to accommodate the different needs of students with varying levels of prior knowledge, goal orientation, and cognitive preference in a supportive learning system are provided based on the results.     

Effects of different ratios of worked solution steps and problem solving opportunities on cognitive load and learning outcomes

A crucial challenge for instructional designers is to determine the amount of support that is most beneficial for learning. This experiment investigated effects of different ratios of worked solution steps (high assistance) and to-be-solved problem steps (low assistance) on cognitive skill acquisition in geometry. High-school students (N = 125) worked on a geometry lesson in a Cognitive Tutor under five different ratios (from zero worked steps and five to-be-solved steps to four worked steps and one to-be-solved step). Effects on cognitive load and learning outcomes were assessed. We expected the effectiveness of different ratios to vary with the type of learning outcomes (i.e., procedural vs. conceptual knowledge) and the difficulty of the to-be-learned principles. Results showed that for procedural knowledge (but not for conceptual knowledge) problem solving alone was most beneficial for the acquisition of procedural knowledge related to an easy principle. For a difficult principle, no ratio of worked steps and problem solving showed an advantage over another. Problem solving induced more extraneous load than studying worked examples. Thus, in determining optimal amounts of guidance type of knowledge and difficulty of the single to-be learned knowledge chunks should be considered.     

Cognitive load and science text comprehension: Effects of drawing and mentally imagining text content

One hundred and eleven 10th graders read an expository science text on the dipole character of water molecules (ca. 1600 words). Reading instruction was varied according to a 2 × 2 experimental design with factors ‘drawing pictures of text content on paper’ (yes, no) and ‘mentally imagining text content while reading’ (yes, no). The results indicate that drawing pictures, mediated through increased cognitive load, decreased text comprehension and, thus, learning (d = −0.37), whereas mental imagery, although decreasing cognitive load, increased comprehension only when students did not have to draw pictures simultaneously (d = 0.72). No evidence was found that the effects were moderated by domain-specific prior knowledge, verbal ability, or spatial ability. The results are in line with cognitive theories of multimedia learning, self-regulated learning, and mental imagery as well as conceptions of science learning that focus on promoting mental model construction by actively visualizing the content to be learned. Constructing mental images seems to reduce cognitive load and to increase comprehension and learning outcome when the mental visualization processes are not disturbed by externally drawing pictures on paper, whereas drawing pictures seems to increase cognitive load resulting in reduced comprehension and learning outcome.     

The effects of video on cognitive load and social presence in multimedia-learning

Two studies examined the use of video in multimedia learning environments. In Study 1, participants (N = 26) viewed one of two versions of a computer-based multimedia presentation: video, which included a video of a lecture with synchronized slides, or no video, which included the slides but only an audio narration of the lecture. Learning, cognitive load and social presence were assessed, but a significant difference was found only for cognitive load, with video experiencing greater cognitive load, t (24) = 2.45, p < .05. In Study 2, students (N = 25) were randomly assigned to either video or no video condition. Background knowledge and visual/verbal learning preference were assessed before viewing the presentation, and learning, cognitive load, and social presence were assessed after viewing. No significant differences were found for learning or social presence. However, a significant visual/verbal learning preference by condition interaction was found for cognitive load, F (1,21) = 4.51, p < .05: low visual-preference students experienced greater cognitive load in the video condition, while high visual-preference students experienced greater cognitive load in the no video condition.     

Learning goal hierarchies from structured observations and expert annotations

We describe a relational learning by observation framework that automatically creates cognitive agent programs that model expert task performance in complex dynamic domains. Our framework uses observed behavior and goal annotations of an expert as the primary input, interprets them in the context of background knowledge, and returns an agent program that behaves similar to the expert. We map the problem of creating an agent program on to multiple learning problems that can be represented in a “supervised concept learning’’ setting. The acquired procedural knowledge is partitioned into a hierarchy of goals and represented with first order rules. Using an inductive logic programming (ILP) learning component allows our framework to naturally combine structured behavior observations, parametric and hierarchical goal annotations, and complex background knowledge. To deal with the large domains we consider, we have developed an efficient mechanism for storing and retrieving structured behavior data. We have tested our approach using artificially created examples and behavior observation traces generated by AI agents. We evaluate the learned rules by comparing them to hand-coded rules. Editor: Rui Camacho     

Building virtual cities,inspiring intelligent citizens: Digital games for developing students’ problem solving and learning motivation

This study investigates the effectiveness digital game-based learning (DGBL) on students’ problem solving, learning motivation, and academic achievement. In order to provide substantive empirical evidence, a quasi-experimental design was implemented over the course of a full semester (23 weeks). Two ninth-grade Civics and Society classes, with a total of 44 students (15–16 years old), were randomly assigned to one of two conditions: an experimental group (incorporating DGBL) and a comparison group (taught using traditional instruction). Two-way mixed ANOVA was employed to evaluate changes in problem solving ability and compare the effectiveness the two strategies, while ANCOVA was used to analyze the effects on learning motivation and academic achievement. The results of this study are summarized as follows: (1) The DGBL strategy was clearly effective in promoting students’ problem solving skills, while the control group showed no improvement. Additionally, data from the mid-test and post-test demonstrate that, as a higher order thinking skill, problem-solving requires a full semester to develop. (2). DGBL resulted in better learning motivation for students in the experimental group as compared to learners receiving TI. (3) Contrary to some suggestions that digital games could inhibit academic achievement, no statistically significant difference was found between the two groups. Most importantly, the quantitative improvement in problem-solving and learning motivation suggest that DGBL can be exploited as a useful and productive tool to support students in effective learning while enhancing the classroom atmosphere. Future research in DGBL should emphasize the evaluation of other higher order elements of the cognitive domain in terms of academic achievement outcomes and skills, such as critical and creative thinking.     

Improving problem solving ability in mathematics by using a mathematical model: A computerized approach

The present study investigates the improvement of students’ mathematical performance by using a mathematical model through a computerized approach. We had developed an intervention program and 11 years students worked independently on a mathematical model in order to improve their self-representation in mathematics, to self-regulate their performance and consequently to improve their problem solving ability. The emphasis of using the specific model was on dividing the problem solving procedure into stages, the concentration on the students’ cognitive processes at each stage and the self-regulation of those cognitive processes in order to overcome cognitive obstacles. The use of the computer offered the opportunity to give students general comments, hints and feedback without the involvement of their teachers. Students had to communicate with a cartoon animation presenting a human being who faced difficulties and cognitive obstacles during problem solving procedure. Three tools were constructed for pre- and post-test (self-representation, mathematical performance and self-regulation). There were administered to 255 students (11 years old), who constituted the experimental and the control group. Results confirmed that providing students with the opportunity to self-reflect on their learning behavior when they encounter obstacles in problem solving is one possible way to enhance students’ self-regulation and consequently their mathematical performance.     

The effects of time-compressed instruction and redundancy on learning and learners’ perceptions of cognitive load

Can increasing the speed of audio narration in multimedia instruction decrease training time and still maintain learning? The purpose of this study was to examine the effects of time-compressed instruction and redundancy on learning and learners’ perceptions of cognitive load. 154 university students were placed into conditions that consisted of time-compression (0%, 25%, or 50%) and redundancy (redundant text and narration or narration only). Participants were presented with multimedia instruction on the human heart and its parts then given factual and problem solving knowledge tests, a cognitive load measure, and a review behavior (back and replay buttons) measure. Results of the study indicated that participants who were presented 0% and 25% compression obtained similar scores on both the factual and problem solving measures. Additionally, they indicated similar levels of cognitive load. Participants who were presented redundant instruction were not able to perform as well as participants presented non-redundant instruction.     

The educational affordances of blogs for self-directed learning

To be successful university learners, students need to develop skills in self-directed learning. This encompasses a range of cognitive and meta-cognitive skills including generating one’s own learning goals, planning how to tackle a problem, evaluating whether learning goals have been met, and re-planning based on this evaluation. The educational affordances of blogs offer opportunities for students to become self-directed learners in a supportive social environment. Based on qualitative analysis of design diaries written by 113 computer science students about a creative project, this paper presents a framework of the ways in which blogging activities can assist groups of students and their teachers in the development of a range of cognitive, social and self-directed learning skills. Although the students in this study used the commenting feature of blogs effectively for the purpose of praising and encouraging their peers, and giving hints and tips for solving problems, they did not coach each other on higher order skills. The paper discusses how this could be achieved in order to extend the educational value of blogging within a university learning community.     

From learning to new goal generation in a bioinspired robotic setup

In the field of cognitive bioinspired robotics, we focus on autonomous development, and propose a possible model to explain how humans generate and pursue new goals that are not strictly dictated by survival. Autonomous lifelong learning is an important ability for robots to make them able to acquire new skills, and autonomous goal generation is a basic mechanism for that. The Intentional Distributed Robotic Architecture (IDRA) here presented intends to allow the autonomous development of new goals in situated agents starting from some simple hard-coded instincts. It addresses this capability through an imitation of the neural plasticity, the property of the cerebral cortex supporting learning. Three main brain areas are involved in goal generation, cerebral cortex, thalamus, and amygdala; these are mimicked at a functional level by the modules of our computational model, namely Deliberative, Working-Memory, Goal-Generator, and Instincts Modules, all connected in a network. IDRA has been designed to be robot independent; we have used it in simulation and on the real Aldebaran NAO humanoid robot. The reported experiments explore how basic capabilities, as active sensing, are obtained by the architecture.     

Advancing young adolescents’ hypothesis-development performance in a computer-supported and problem-based learning environment

Hypothesis development is a complex cognitive activity, but one that is critical as a means of reducing uncertainty during ill-structured problem solving. In this study, we examined the effect of metacognitive scaffolds in strengthening hypothesis development. We also examined the influence of hypothesis development on young adolescents’ problem-solving performance. Data was collected from sixth-grade students (N = 172) using a computer-supported problem-based learning environment, Animal Investigator. The findings of the study indicated that participants using metacognitive scaffolds developed significantly better hypotheses and that hypothesis-development performance was predictive of solution-development performance. This article discusses further educational implications of the findings and future research.     

The effects of source representation and goal instructions on college students' information evaluation behavior change

We investigated ways of scaffolding information evaluation behavior (IEB) in online inquiry contexts. Previous instructional support simplified IEB and rarely critically addressed the cognitive load that accompanies multiple representations or naïve task perception that hinders critical evaluation. We conducted a longitudinal, 2 × 2 quasi-experimental study in an introductory college biology course, varying (A) Source Representation Scaffolds to address limited cue awareness and cognitive load and (B) Goal Instructions to address task perception. For treatment A, students were given an annotation tool in addition to a checklist (Control A). For treatment B, instead of persuasion goal instructions (Control B), written task directions prompted student to consider alternative ideas (balanced reasoning goals). We measured students' IEB four times. We also measured individual task perception and cognitive capacity. Multilevel analyses identified the specific nature of changes in IEB. On average, IEB did not improve much in the baseline group while task perception and cognitive capacity differentiated IEB scores. Conversely, both annotation and balanced reasoning goals yielded improved gains in IEB, but there was a negative interaction effect when they were combined. The results demonstrate the benefits of annotation and balanced reasoning goals but suggest the need to address possible difficulties in using multiple scaffolds.     

Can the use of cognitive and metacognitive self-regulated learning strategies be predicted by learners’ levels of prior knowledge in hypermedia-learning environments?

Research on self-regulated learning (SRL) in hypermedia-learning environments is a growing area of interest, and prior knowledge can influence how students interact with these systems. One hundred twelve (N = 112) undergraduate students’ interactions with MetaTutor, a multi-agent, hypermedia-based learning environment, were investigated, including how prior knowledge affected their use of SRL strategies. We expected that students with high prior knowledge would engage in significantly more cognitive and metacognitive SRL strategies, engage in different sequences of SRL strategies, spend more time engaging in SRL processes, and visit more pages that were relevant to their sub-goals than students with low prior knowledge. Results showed significant differences in the total use of SRL strategies between prior knowledge groups, and more specifically, revealed significant differences in the use of each metacognitive strategy (e.g., judgment of learning), but not each cognitive strategy (e.g., taking notes) between prior knowledge groups. Results also revealed different sequences of use of SRL strategies between prior knowledge groups, and that students spent different amounts of time engaging in SRL processes; however, all students visited similar numbers of relevant pages. These results have important implications on designing multi-agent, hypermedia environments; we can design pedagogical agents that adapt to students’ learning needs, based on their prior knowledge levels.     

Predicting college students’ online information searching strategies based on epistemological,motivational, decision-related,and demographic variables

This study examines the extent to which epistemological, motivational, decision-related, and demographic variables predict college students' use of online information searching strategies (behavioural, procedural, and metacognitive strategies). The participants included preservice teachers (N = 538) from 13 universities in different parts of Turkey. Stepwise multiple regression analyses were conducted to identify the variables predicting each online information searching strategy. The results revealed that online information searching strategies were best predicted by epistemological beliefs and then decision-making styles, web search experience, and goal orientations. Students who had advanced epistemological beliefs in speed of learning tended to have better behavioural, procedural, and metacognitive strategies, while students having naive epistemological beliefs in ability to learn had lower level online searching strategies. Students having more web search experience had better online searching strategies. Additionally, as the level of students’ mastery-approach goals increases, the use of procedural and metacognitive domain strategies increase as well, while the increase in the level of mastery-avoidance goals were related to the use of less behavioural domain strategies. Finally, students having rational decision styles were more likely to use higher levels of online information searching strategies, while students with avoidant styles tended to use less behavioural and procedural domain strategies.     

Effects of mental process integrated nursing training using mobile device on students’ cognitive load,learning attitudes,acceptance, and achievements

Clinical nursing training is important to nursing educators and student nurses in nursing education since safe and competent care depends on good clinical problem solving skills. Therefore, developing better cognitive problem-solving strategies or tools are essential for clinical nursing practices. Moreover, learning diagnosis is also a critical determinant in the acquisition, processing, and application of clinical skills in nursing practices. Bearing this in mind, this study aims to develop a mobile interactive learning and diagnosis (MILD) system to support problem-based learning (PBL) in a clinical nursing course based on the testing-based approach. Using mobile devices as a learning tool to integrate both real-world and digital-world resources for students and adopting PBL as a learning strategy to facilitate the development of the clinical problem solving skills. To show the effectiveness of the proposed approach, an experiment was conducted in a foundations of nursing course at a nursing college in Taiwan. The experimental results show that the proposed approach is helpful to students in improving learning performance and reducing cognitive loads. Moreover, it was also found that most students showed positive perceptions toward the usage of the proposed system.     

Does cognitive load moderate the seductive details effect? A multimedia study

Several studies have shown that adding seductive details to instructional materials has a detrimental effect on learning. However, other studies have shown non-significant findings. The present study uses cognitive load theory as a theoretical framework to explain these controversial results in seductive details research. Using a 2 × 2 experimental design we asked a group of high-school students (N = 100) to learn about biology with a multimedia environment that manipulated the presence of seductive details (with vs. without) and the modality of the verbal information (high load, on-screen text vs. low load, narration). The findings showed that students’ learning performance was significantly higher when seductive details were presented under the low load condition (narration) as compared to all other conditions. The theoretical implications for understanding the effects of non-redundant and interesting, but irrelevant learning material are discussed and future research directions are presented.     

A hybrid approach to promoting students’ web-based problem-solving competence and learning attitude

Fostering problem-solving abilities has long been recognized as an important issue in education; however, past studies have shown that it is difficult and challenging to find effective learning strategies or tools for improving students’ problem-solving abilities. To cope with this problem, in this study, a hybrid approach that integrates the cognitive apprenticeship model with the collaborative learning strategy is proposed for conducting web-based problem-solving activities. Students’ problem-solving performance is examined in such a hybrid learning context. Furthermore, past studies indicate that cognitive load could affect learners’ performance; thus, the influence of cognitive load on students’ problem-solving effectiveness with this new approach is investigated in depth. The experimental results show that middle- and low-achievement students in the experimental group gained significant benefits from the hybrid approach in comparison with those who learned with the traditional approach. Accordingly, a discussion of how to accommodate the needs of different learning ability groups is provided.     

A conceptual framework mapping the application of information search strategies to well and ill-structured problem solving

Problem-based learning (PBL) is an instructional approach that is organized around the investigation and resolution of problems. Problems are neither uniform nor similar. 11 and 12 in his design theory of problem solving has categorized problems into two broad types – well-structured and ill-structured. He has also described a host of mediating skills that impact problem solving outcomes. The thrust of this paper rests in the argument that the basis of these mediating skills is information search literacy and particularly, in view of the utility of the Internet as an informational repository, effective information searching skills. This study was an investigation of how different Internet information seeking strategies can be used to engage in problem solving. A conceptual framework that explains how different Internet information searching strategies can be employed in successfully solving well and ill-structured problems was devised and empirically tested. The research site was a newly established polytechnic in Singapore that employs problem-based learning to support its curricular implementation. The sample population of students came from a class of 25 first-year students. The research findings of this study inform that information searching skills indeed play an important role in problem solving. The findings affirm the need for students to be systematically instructed in the skills of information searching to be able to accomplish problem solving. The information searching necessary for solving well-structured problems is constrained and readily manageable. Thus, students only have to be acquainted with fundamental information searching skills to solve well-structured problems. On the other hand, the information needs of ill-structured problems are usually complex, multi-disciplinary and expansive. Hence, students have to be trained to apply a more advanced set of information searching skills in resolving ill-structured problems.     

An analysis of collaborative problem‐solving activities mediated by individual‐based and collaborative computer simulations

Researchers have indicated that the collaborative problem‐solving space afforded by the collaborative systems significantly impact the problem‐solving process. However, recent investigations into collaborative simulations, which allow a group of students to jointly manipulate a problem in a shared problem space, have yielded divergent results regarding their effects on collaborative learning. Hence, this study analysed how students solved a physics problem using individual‐based and collaborative simulations to understand their effects on science learning. Multiple data sources including group discourse, problem‐solving activities, learning test scores, and questionnaire feedback were analysed. Lag sequential analysis on the data found that students using the two simulations collaborated with peers to solve the problem in significantly different patterns. The students using the collaborative simulations demonstrated active engagement in the collaborative activity; however, they did not transform discussions into workable problem‐solving activities. The students using the individual‐based simulation showed a lower level of collaboration engagement, starting with individual exploration of the problem with the simulation, followed by group reflection. The two groups also showed significant differences in their learning test scores. The findings and pedagogical suggestions are discussed in the hope of addressing critical activity design issues in using computer simulations for facilitating collaborative learning.