Implementing Spatial Intelligence-Based Respond Method in the Physics Instruction to Improve Physics Learning Outcomes on the Lesson Subject of Straight Motion of the Tenth Grade Students of SMA N 1 Jogolagan in the First Semester

This study aims at determining influences of the spatial intelligence-based respond method towards physics learning outcomes on the subject of straight motion of the students of Grade X of SMA N 1 Jogonalan. This research also aims at determining whether the implementation of the spatial intelligence-based respond method was better or not when compared with the conventional teaching towards physics learning outcomes on the subject of Straight Motion of the tenth grade students of SMA N 1 Jogonalan. The learning outcomes covered cognitive and affective domains. This research was apparent experimental study using pretest-posttest format and non-equivalent control group design. The sampling used was conditional non-random sampling. The research subject was the students of Grade X of SMA N 1 Jogonalan. This study involved two classes. The experimental class used the spatial intelligence-based respond method while the control class used the conventional method (presentation). Data analysis techniques used regression analysis and an analysis using t test. The testing technique of prerequisite analysis used Normality test, Homogeneity test, Linearity test, Autocorrelation test, Multi con linearity test, and Hetero-skedaticity test. Hypothesis testing technique used F test and t test. Based on the research results, there were positive influences of the spatial intelligence-based respond method towards students’ physics learning outcomes in the domains of cognitive and affective on the subject of straight motion of the tenth grade students of SMA N 1 Jogonalan. The research results also indicated that the teaching using the spatial intelligence-based respond method was better than one using the conventional method on physics learning outcomes in the domains of cognitive and affective on the subject of straight motion of the tenth grade students of SMA N 1 Jogonalan. Keywords : response method, spatial intelligence, straight motion Year : 201

Technical Report for “When People Estimate their Personal Intelligence Who Is Overconfident? Who is Accurate?”

The Technical Supplement includes additional information about the article “Who Believes they are High in Personal Intelligence.” The Supplement is organized such that material follows the organization of the article, with the exception that group-wise analyses—i.e., analyses based on median splits of the archival samples on the Test of Personal Intelligence and Self-Estimated Personal Intelligence, are in their own Appendix owing to the considerable length of that material

A Closer Look at the Test of Personal Intelligence Presentation

Personal intelligence is the capacity to reason about personality and personality-related information. To understand more about the structure of the mental abilities involved in personal intelligence, we fit several factor models to an ability based test of personal intelligence. A two-factor oblique simple structure model fit the data well. The findings inform us about the nature of abilities people use to understand personality in themselves and others

Learning, Social Intelligence and the Turing Test - why an "out-of-the-box" Turing Machine will not pass the Turing Test

The Turing Test (TT) checks for human intelligence, rather than any putative general intelligence. It involves repeated interaction requiring learning in the form of adaption to the human conversation partner. It is a macro-level post-hoc test in contrast to the definition of a Turing Machine (TM), which is a prior micro-level definition. This raises the question of whether learning is just another computational process, i.e. can be implemented as a TM. Here we argue that learning or adaption is fundamentally different from computation, though it does involve processes that can be seen as computations. To illustrate this difference we compare (a) designing a TM and (b) learning a TM, defining them for the purpose of the argument. We show that there is a well-defined sequence of problems which are not effectively designable but are learnable, in the form of the bounded halting problem. Some characteristics of human intelligence are reviewed including it's: interactive nature, learning abilities, imitative tendencies, linguistic ability and context-dependency. A story that explains some of these is the Social Intelligence Hypothesis. If this is broadly correct, this points to the necessity of a considerable period of acculturation (social learning in context) if an artificial intelligence is to pass the TT. Whilst it is always possible to 'compile' the results of learning into a TM, this would not be a designed TM and would not be able to continually adapt (pass future TTs). We conclude three things, namely that: a purely "designed" TM will never pass the TT; that there is no such thing as a general intelligence since it necessary involves learning; and that learning/adaption and computation should be clearly distinguished.Comment: 10 pages, invited talk at Turing Centenary Conference CiE 2012, special session on "The Turing Test and Thinking Machines

A closer look at the Test of Personal Intelligence (TOPI)

Personal intelligence involves the capacity to reason about personality and personality-related information. Studying ability-based measures of personal intelligence creates a virtuous cycle of better measurement and better theoretical understanding. In Study 1 (N = 10,318), we conduct an item-level analysis of the Test of Personal Intelligence (TOPI) to explore people\u27s problem-solving abilities in the area. Personal intelligence divided into a Consistency-Congruency factor that concerned understanding traits and their associated behaviors, and a Dynamic-Analytic factor that involved understanding personality processes and goals. The finding cross-validated in Study 2 (N = 8,459). In Study 3 (N = 384), we examined correlates of the two factors. Understanding the abilities involved in personal intelligence may help us to educate people about how to better solve problems about personality

Saudi normative data for the Wisconsin Card Sorting Test, Stroop Test, Test of Non-verbal Intelligence-3, Picture Completion and Vocabulary (subtest of the Wechsler Adult Intelligence Scale-Revised).

There are 2 aims for this study: first, to collect normative data for the Wisconsin Card Sorting Test (WCST), Stroop test, Test of Non-verbal Intelligence (TONI-3), Picture Completion (PC) and Vocabulary (VOC) sub-test of the Wechsler Adult Intelligence Scale-Revised for use in a Saudi Arabian culture, and second, to use the normative data provided to generate the regression equations. To collect the normative data and generate the regression equations, 198 healthy individuals were selected to provide a representative distribution for age, gender, years of education, and socioeconomic class. The WCST, Stroop test, TONI-3, PC, and VOC were administrated to the healthy individuals. This study was carried out at the Department of Clinical Neurosciences, Riyadh Military Hospital, Riyadh, Kingdom of Saudi Arabia from January 2000 to July 2002. Normative data were obtained for all tests, and tables were constructed to interpret scores for different age groups. Regression equations to predict performance on the 3 tests of frontal function from scores on tests of fluid (TONI-3) and premorbid intelligence were generated from the data from the healthy individuals. The data collected in this study provide normative tables for 3 tests of frontal lobe function and for tests of general intellectual ability for use in Saudi Arabia. The data also provide a method to estimate preinjury ability without the use of verbally based tests

Application of Natural Language Processing and Evidential Analysis to Web-Based Intelligence Information Acquisition

The quality of decisions made in business and government relates directly to the quality of the information used to formulate the decision. This information may be retrieved from an organization's knowledge base (Intranet) or from the World Wide Web. Intelligence services Intranet held information can be efficiently manipulated by technologies based upon either semantics such as ontologies, or statistics such as meaning-based computing. These technologies require complex processing of large amount of textual information. However, they cannot currently be effectively applied to Web-based search due to various obstacles, such as lack of semantic tagging. A new approach proposed in this paper supports Web-based search for intelligence information utilizing evidence-based natural language processing (NLP). This approach combines traditional NLP methods for filtering of Web-search results, Grounded Theory to test the completeness of the evidence, and Evidential Analysis to test the quality of gathered information. The enriched information derived from the Web-search will be transferred to the intelligence services knowledge base for handling by an effective Intranet search system thus increasing substantially the information for intelligence analysis. The paper will show that the quality of retrieved information is significantly enhanced by the discovery of previously unknown facts derived from known facts

Faith in the Algorithm, Part 1: Beyond the Turing Test

Since the Turing test was first proposed by Alan Turing in 1950, the primary goal of artificial intelligence has been predicated on the ability for computers to imitate human behavior. However, the majority of uses for the computer can be said to fall outside the domain of human abilities and it is exactly outside of this domain where computers have demonstrated their greatest contribution to intelligence. Another goal for artificial intelligence is one that is not predicated on human mimicry, but instead, on human amplification. This article surveys various systems that contribute to the advancement of human and social intelligence