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Student involvement in their own assessment can add reflection and metacognition to the learning process. Based on this idea, an assessment instrument was developed to self-assess college students' mathematical problem solving tasks. The main objective of this exercise is to improve student learning. The assessment instrument contains three items: student opinion questionnaire, an analytic evaluation rubric, and a self assessment schedule. A peer assessment component was also included in the assessment process to gain more accuracy. The rubric will serve three main purposes. First, students can use the rubric as a learning tool. Second, it will serve as a teaching tool for teachers. Third, it can be used as an assessment tool. However, the whole purpose is to improve student learning rather than providing them with a letter grade.

The purpose of this study was to investigate the relationship between a student's stated preference for solving a problem and his/her actual problem solving methodology. Approximately 116 science students between the ages of 15 and 22 were given an 18 item abstract preference survey. Each student was interviewed and given the opportunity to solve three different tasks: (1) fossil identification; (2) a balance problem; and (3) an electrical circuit problem. Results included the following: (1) considering all tasks, there was a similarity in performances of males and females; (2) on tasks involving the fossil and electrical circuit, the shift of preference was from a concrete mode to an abstract mode; (3) on the balance task, the shift of preference was from abstract to concrete; (4) college students were less likely to shift preferences; and (5) students' preferences for solving a hypothetical model may quickly change when the problem is real. (RH)

Upper elementary students are the focus of this paper, intended to present a few studies that have been done in the past five years that are related to two aspects of problem solving: strategies used by the problem solver and tasks used in studying problem solving. The review is not intended to be exhaustive, but is designed to present examples of strategies and tasks that have been studied or used in recent research. (MP)

The performance of children on problem-solving tasks 8 years after their participation in an early education intervention was compared with that of children who did not receive the intervention. At the time of the outcome assessment, all subjects (n=60) were in middle school. One group of the subjects was selected from the middle school students in a school system in a northeastern industrial city who had attended the school system since kindergarten; the other subject group had been selected when in kindergarten to receive an intervention based on a task analysis of curricula into steps necessary for mastery of the activity. It had previously been shown that the treatment group scored at a significantly higher level on standardized achievement tests than did a comparison group drawn from the same pool of at-risk kindergarten students. Three problem-solving tasks from Piagetian and mathematics curriculum research were administered. The performance of both groups was comparable with age-related results in the literature, but the treatment group surpassed the other cohort on two of the three tasks. Every subject in the treatment group solved at least one task; 11 of the cohort group solved none. Implications for the teaching of learning strategies are discussed. The instructions for the tasks, some task diagrams, and four tables of results are included. (SLD)

This systematic review aims to examine the impact cognitive strategies have on psychological and neuropsychological tasks performance. Cognitive strategies are organized through heuristics and biases, automating a set of activities that involves information processing and optimizing the use of cognitive resources. However, this whole process depends on the quality of the information, a peculiarity that depends on multiple intra-individual factors of a psychological, psychiatric and neurological nature. If there are changes that impact the quality of the information that accesses the automated systems, this will result in biased decision making and that will potentially produce an inadequate response from the individual, leading to unwanted consequences.

Investigated, within a Piagetian framework, was the degree of abstract preferences exhibited by five different grade levels of science students as they completed eighteen problem solving tasks. Three hundred twenty-nine randomly selected students from five grade levels, ranging from eighth grade to college seniors, were given the Shipley Test of Abstract Reasoning. Groups of concrete and formal operational students were identified as were groups based on sex and grade level. Solutions for each task were ranked according to degree of abstraction represented. Correlations were completed to determine, for each group, the relationship between abstract ability and abstract preferences. Older groups demonstrated greater abstract reasoning ability. No significant differences were found between grade levels with respect to abstract preference scores. This study supported the assumptions that a student's level of reasoning is often below his capacity and that a student's preference toward a specific solution may, in part, be responsible for his below-capacity functioning. (LS)

A STUDY INVESTIGATED THE RELATION BETWEEN PERFORMANCE ON LEARNING AND PROBLEM-SOLVING TASKS AND LEVEL OF INTELLIGENCE. PERFORMANCE WAS MEASURED ACROSS A SERIES OF 10 LEARNING AND PROBLEM-SOLVING TASKS PRESENTED TO SUBJECTS IN A SERIES OF SIX FILMS SHOWN IN A CLASSROOM. THE SUBJECTS WERE 275 JUNIOR HIGH SCHOOL STUDENTS AND 109 FOURTH GRADERS CLASSIFIED AS BRIGHT, NORMAL, OR DULL. THE BRIGHT STUDENTS WERE UPPER-MIDDLE CLASS AND THE DULL STUDENTS LOWER-MIDDLE OR LOWER CLASS. NO HYPOTHESES WERE PUT FORWARD, BUT THE TASKS WERE CONSTRUCTED TO REQUIRE A NUMBER OF PSYCHOLOGICAL PROCESSES. THE RESULTS SHOWED THAT BRIGHTER STUDENTS OUTSCORED THEIR AGE PEERS IN ALL TASKS. COMPARISON BETWEEN DULL SEVENTH GRADERS AND BRIGHT FOURTH GRADERS SHOWED WIDE VARIATION IN ABILITIES. THE DULL SEVENTH GRADERS SHOWED EXTREMELY POOR PERFORMANCE ON THE ANAGRAMS AND VERBAL MEMORY TASKS. IT IS POSSIBLE THAT THE TESTING SITUATION INDUCED THE VERY LOW SCORES IN THIS GROUP. TASK INTERCORRELATIONS FOR EACH GROUP OF SUBJECTS WERE COMPUTED. (DK)

This study explores the use generative AI technologies by teachers for professional information problem solving (IPS) tasks, with a specific focus on the creation of digital educational materials. Traditionally, educational practitioners and instructional designers have relied on established IPS frameworks, such as the IPS-I model by Brand-Gruwel et al. (2009), to guide the development of IPS learning objectives within their learning environments. However, with the advent of generative AI tools like ChatGPT, information search and processing strategies have undergone a significant transformation (Dehouche, 2021), prompting a reevaluation of traditional IPS models. This change demands a critical reassessment and evolution of these models to better reflect the impact and dynamics of these technological advancements in educational settings. Our research explores the strategies that teachers use when processing and presenting information while using generative AI during professional IPS tasks, specifically in the design of digital educational materials. To achieve this, we use a combination of think-aloud and cued retrospective recall protocols. This research aims to identify the necessary competencies for leveraging generative AI effectively in professional settings. Our findings will set the stage for proposing an innovative 'IPS 2.0 model' designed to incorporate the transformative effects of generative AI technologies on professional IPS tasks. We seek to extend the theoretical and practical frameworks that underpin IPS in education so that they remain relevant and effective in an era of rapid technological change. The insights gained from the study will inform the development of targeted instructional interventions for developing teachers' IPS competence in a generative AI-era, facilitating the effective and innovative use of AI in education.

Preference scores were determined for several different groups of students ranging in age from seven to adult. In addition, instruments were administered to determine the cognitive level at which the students were capable of functioning. Comparisons between the students' cognitive level and preferences were made. The results indicated that the students' preference to a method of solving a problem was independent of the cognitive level of development. However, the data support the premise that preferences may be task dependent. Children who are only capable of functioning at the concrete level of operations frequently prefer to attempt to solve problems in a manner through which they are not capable of success. Further, formal operational children frequently prefer to solve problems in a concrete manner. A possible explanation is that they feel that the concrete mode will either be easier or more fun; additional research, however, will be needed to confirm this explanation. Another aspect of these studies compared the manner in which students actually began to solve a problem with a previously stated preference. It was found that the overall "consistent score" for both groups was similar; formal students, however, were generally more successful in solving the problems. (References and tables are included.) (Author)

This study aimed to investigate the effects of authentic tasks on preschool preservice teachers' attitudes towards the course and problem solving skills. The study was designed in accordance with the pretest-posttest control group model. The data were collected by using the "Problem Solving Skills Inventory", the "Course Attitude Scale", and the "Structured Interview Form" to obtain participant views about the process. The study was conducted with a total of 100 third-year preservice teachers who were enrolled in the course "Special Education Methods I" at Marmara University Ataturk Faculty of Education's Preschool Education Department during the 2010-2011 academic year. Of these participants, 35 were in the experimental group, 35 in the 1st control group and 30 in the 2nd control group. The results showed a positive significant difference in the attitudes of the experimental group towards classes and their problem solving skills perceptions at the end of the experiment, while no such difference was observed in the two control groups. The responses to the interview forms included positive views regarding the process of using authentic tasks from the experimental group, but mostly negative views from the two control groups who underwent traditional instruction. The tasks used in the experimental group in order to develop problem solving skills and recognize professional problems and solutions improved preservice teachers' problem solving perceptions and attitudes towards classes.

Just-In-Time Learning (JIT Learning) is a semester-long graduate course that teaches corporate trainers and instructional designers how to design performance improvement interventions. This course is part of a Master's program in Instructional Technology at San Francisco State University. The course has been offered three times and has been completed by a total of 38 people. Learners produce two major deliverables for this course: a paper describing a performance problem and the design of a system to address the problem, and a shorter paper explaining the design strategy. Based on final grades for the course, participants in this class can be grouped into three broad categories. The A-level performers are 38% of the total students, B-level are 17%, and C-level are 45%. An Electronic Performance Support System (EPSS) was designed and implemented to help the B-level and C-level people improve their performance. The JIT Learning EPSS was designed and developed by Infomark Software Corporation with CGM Communications and assistance from several graduate students in the Department in the first half of 2001. The JIT Learning EPSS was implemented with 15 learners in Fall 2001. For this class the grade distribution was 53% in the A-level, 20% in the B-level, and 27% in the C-level. When compared with prior classes, all of the B-level performers improved to A-level and half of the C-level improved to B-level. A formative evaluation of the system was conducted in the winter of 2002. The results suggest that the remaining C-level performers do not have a sufficient mental model of the design task. The next version of the software will focus on helping users develop and assess their mental models before they begin the design task. Includes three color figures. (Author/AEF)

This conceptual paper discusses two frameworks, developed independently by the lead author, that will provide the conceptual foundation for the identification and evaluation of mental computation strategies students demonstrate during an upcoming research project entitled Mental Computation in Year 5. These frameworks will be used by the lead author during an intervention to investigate the application of mental computation strategies in problem solving tasks involving duration of time. It is an intended outcome of the project that the two frameworks will be useful for teachers and students in upper primary school to provide feedback regarding the teaching and learning of mental computation.

Student learning is greatest in classrooms where students engage in problem solving tasks that are cognitively demanding. However, there are growing concerns that many Australian students are given limited opportunities to engage in these types of tasks. 108 upper primary school teachers were surveyed to examine task features and cognitive demand of problem solving tasks. Teachers are found to favour tasks with lower-level cognitive demand above those with higher-level cognitive demand when developing problem solving proficiency.