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1ERIC ED616609: Human Resource Management Variables And Academic Staff Job Effectiveness In The University Of Calabar, Cross River State, Nigeria The Study Examined Some Human Resource Management Variables And Academic Staff Job Effectiveness In The University Of Calabar In Cross River State, Nigeria. To Achieve The Aim Of This Study, Two Research Questions Were Raised And Two Hypotheses Were Formulated To Guide The Study. A Correlational Research Design Was Adopted For The Study. The Population Of The Study Comprises All The Academic Staff In The University Of Calabar. The Total Number Of All The Academic Staff Is Three Thousand Eight Hundred And Sixty (3860). A Stratified Random Sampling Technique Was Used To Select Total Numbers Of One Hundred (100) Respondents From The University Of Calabar. Relevant Data For The Study Was Collected With A Researcher-developed Questionnaire Titled: "Human Resource Management Variable And Academic Staff Job Effectiveness Questionnaire" (HRMVASJEQ). The Instrument Was Subjected To Face And Content Validity By Experts In The Administration Of Higher Education And Measurement And Evaluation, Faculty Of Education, University Of Calabar. The Pearson Product Moment Correlation Analysis With The Aid Of The Statistical Package For Social Science (SPSS) Version 25, Was Used For Data Analysis. The Result Revealed That The Management Of Lecturers' Appraisal/promotion And Management Of Lecturers' In-service Training Significantly Relate To Their Job Effectiveness In The University. It Was Recommended That The University Management Should Ensure That Lecturers Are Appraised And Promoted Appropriately To Enhance Their Lecturer Job Performance. Also, That The University Management Should Make Provision For Lecturer In-service Training To Enhance Learning And Improving Lecturers' Job Effectiveness.

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The study examined some human resource management variables and academic staff job effectiveness in the university of Calabar in Cross River State, Nigeria. To achieve the aim of this study, two research questions were raised and two hypotheses were formulated to guide the study. A correlational research design was adopted for the study. The population of the study comprises all the academic staff in the University of Calabar. The total number of all the academic staff is three thousand eight hundred and sixty (3860). A stratified random sampling technique was used to select total numbers of one hundred (100) respondents from the University of Calabar. Relevant data for the study was collected with a researcher-developed questionnaire titled: "Human Resource Management Variable and Academic Staff Job Effectiveness Questionnaire" (HRMVASJEQ). The instrument was subjected to face and content validity by experts in the administration of higher education and measurement and evaluation, Faculty of Education, University of Calabar. The Pearson Product Moment Correlation Analysis with the aid of the statistical package for social science (SPSS) version 25, was used for data analysis. The result revealed that the management of lecturers' appraisal/promotion and management of lecturers' in-service training significantly relate to their job effectiveness in the university. It was recommended that the university management should ensure that lecturers are appraised and promoted appropriately to enhance their lecturer job performance. Also, that the university management should make provision for lecturer in-service training to enhance learning and improving lecturers' job effectiveness.

“ERIC ED616609: Human Resource Management Variables And Academic Staff Job Effectiveness In The University Of Calabar, Cross River State, Nigeria The Study Examined Some Human Resource Management Variables And Academic Staff Job Effectiveness In The University Of Calabar In Cross River State, Nigeria. To Achieve The Aim Of This Study, Two Research Questions Were Raised And Two Hypotheses Were Formulated To Guide The Study. A Correlational Research Design Was Adopted For The Study. The Population Of The Study Comprises All The Academic Staff In The University Of Calabar. The Total Number Of All The Academic Staff Is Three Thousand Eight Hundred And Sixty (3860). A Stratified Random Sampling Technique Was Used To Select Total Numbers Of One Hundred (100) Respondents From The University Of Calabar. Relevant Data For The Study Was Collected With A Researcher-developed Questionnaire Titled: "Human Resource Management Variable And Academic Staff Job Effectiveness Questionnaire" (HRMVASJEQ). The Instrument Was Subjected To Face And Content Validity By Experts In The Administration Of Higher Education And Measurement And Evaluation, Faculty Of Education, University Of Calabar. The Pearson Product Moment Correlation Analysis With The Aid Of The Statistical Package For Social Science (SPSS) Version 25, Was Used For Data Analysis. The Result Revealed That The Management Of Lecturers' Appraisal/promotion And Management Of Lecturers' In-service Training Significantly Relate To Their Job Effectiveness In The University. It Was Recommended That The University Management Should Ensure That Lecturers Are Appraised And Promoted Appropriately To Enhance Their Lecturer Job Performance. Also, That The University Management Should Make Provision For Lecturer In-service Training To Enhance Learning And Improving Lecturers' Job Effectiveness.” Metadata:

  • Title: ➤  ERIC ED616609: Human Resource Management Variables And Academic Staff Job Effectiveness In The University Of Calabar, Cross River State, Nigeria The Study Examined Some Human Resource Management Variables And Academic Staff Job Effectiveness In The University Of Calabar In Cross River State, Nigeria. To Achieve The Aim Of This Study, Two Research Questions Were Raised And Two Hypotheses Were Formulated To Guide The Study. A Correlational Research Design Was Adopted For The Study. The Population Of The Study Comprises All The Academic Staff In The University Of Calabar. The Total Number Of All The Academic Staff Is Three Thousand Eight Hundred And Sixty (3860). A Stratified Random Sampling Technique Was Used To Select Total Numbers Of One Hundred (100) Respondents From The University Of Calabar. Relevant Data For The Study Was Collected With A Researcher-developed Questionnaire Titled: "Human Resource Management Variable And Academic Staff Job Effectiveness Questionnaire" (HRMVASJEQ). The Instrument Was Subjected To Face And Content Validity By Experts In The Administration Of Higher Education And Measurement And Evaluation, Faculty Of Education, University Of Calabar. The Pearson Product Moment Correlation Analysis With The Aid Of The Statistical Package For Social Science (SPSS) Version 25, Was Used For Data Analysis. The Result Revealed That The Management Of Lecturers' Appraisal/promotion And Management Of Lecturers' In-service Training Significantly Relate To Their Job Effectiveness In The University. It Was Recommended That The University Management Should Ensure That Lecturers Are Appraised And Promoted Appropriately To Enhance Their Lecturer Job Performance. Also, That The University Management Should Make Provision For Lecturer In-service Training To Enhance Learning And Improving Lecturers' Job Effectiveness.
  • Author:
  • Language: English

“ERIC ED616609: Human Resource Management Variables And Academic Staff Job Effectiveness In The University Of Calabar, Cross River State, Nigeria The Study Examined Some Human Resource Management Variables And Academic Staff Job Effectiveness In The University Of Calabar In Cross River State, Nigeria. To Achieve The Aim Of This Study, Two Research Questions Were Raised And Two Hypotheses Were Formulated To Guide The Study. A Correlational Research Design Was Adopted For The Study. The Population Of The Study Comprises All The Academic Staff In The University Of Calabar. The Total Number Of All The Academic Staff Is Three Thousand Eight Hundred And Sixty (3860). A Stratified Random Sampling Technique Was Used To Select Total Numbers Of One Hundred (100) Respondents From The University Of Calabar. Relevant Data For The Study Was Collected With A Researcher-developed Questionnaire Titled: "Human Resource Management Variable And Academic Staff Job Effectiveness Questionnaire" (HRMVASJEQ). The Instrument Was Subjected To Face And Content Validity By Experts In The Administration Of Higher Education And Measurement And Evaluation, Faculty Of Education, University Of Calabar. The Pearson Product Moment Correlation Analysis With The Aid Of The Statistical Package For Social Science (SPSS) Version 25, Was Used For Data Analysis. The Result Revealed That The Management Of Lecturers' Appraisal/promotion And Management Of Lecturers' In-service Training Significantly Relate To Their Job Effectiveness In The University. It Was Recommended That The University Management Should Ensure That Lecturers Are Appraised And Promoted Appropriately To Enhance Their Lecturer Job Performance. Also, That The University Management Should Make Provision For Lecturer In-service Training To Enhance Learning And Improving Lecturers' Job Effectiveness.” Subjects and Themes:

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Find ERIC ED616609: Human Resource Management Variables And Academic Staff Job Effectiveness In The University Of Calabar, Cross River State, Nigeria The Study Examined Some Human Resource Management Variables And Academic Staff Job Effectiveness In The University Of Calabar In Cross River State, Nigeria. To Achieve The Aim Of This Study, Two Research Questions Were Raised And Two Hypotheses Were Formulated To Guide The Study. A Correlational Research Design Was Adopted For The Study. The Population Of The Study Comprises All The Academic Staff In The University Of Calabar. The Total Number Of All The Academic Staff Is Three Thousand Eight Hundred And Sixty (3860). A Stratified Random Sampling Technique Was Used To Select Total Numbers Of One Hundred (100) Respondents From The University Of Calabar. Relevant Data For The Study Was Collected With A Researcher-developed Questionnaire Titled: "Human Resource Management Variable And Academic Staff Job Effectiveness Questionnaire" (HRMVASJEQ). The Instrument Was Subjected To Face And Content Validity By Experts In The Administration Of Higher Education And Measurement And Evaluation, Faculty Of Education, University Of Calabar. The Pearson Product Moment Correlation Analysis With The Aid Of The Statistical Package For Social Science (SPSS) Version 25, Was Used For Data Analysis. The Result Revealed That The Management Of Lecturers' Appraisal/promotion And Management Of Lecturers' In-service Training Significantly Relate To Their Job Effectiveness In The University. It Was Recommended That The University Management Should Ensure That Lecturers Are Appraised And Promoted Appropriately To Enhance Their Lecturer Job Performance. Also, That The University Management Should Make Provision For Lecturer In-service Training To Enhance Learning And Improving Lecturers' Job Effectiveness. at online marketplaces:


2ERIC ED592694: How Deep Is Knowledge Tracing? In Theoretical Cognitive Science, There Is A Tension Between Highly Structured Models Whose Parameters Have A Direct Psychological Interpretation And Highly Complex, General-purpose Models Whose Parameters And Representations Are Difficult To Interpret. The Former Typically Provide More Insight Into Cognition But The Latter Often Perform Better. This Tension Has Recently Surfaced In The Realm Of Educational Data Mining, Where A Deep Learning Approach To Predicting Students' Performance As They Work Through A Series Of Exercises--termed "deep Knowledge Tracing" Or "DKT"--has Demonstrated A Stunning Performance Advantage Over The Mainstay Of The Field, "Bayesian Knowledge Tracing" Or "BKT." In This Article, We Attempt To Understand The Basis For DKT's Advantage By Considering The Sources Of Statistical Regularity In The Data That DKT Can Leverage But Which BKT Cannot. We Hypothesize Four Forms Of Regularity That BKT Fails To Exploit: Recency Effects, The Contextualized Trial Sequence, Inter-skill Similarity, And Individual Variation In Ability. We Demonstrate That When BKT Is Extended To Allow It More Flexibility In Modeling Statistical Regularities--using Extensions Previously Proposed In The Literature--BKT Achieves A Level Of Performance Indistinguishable From That Of DKT. We Argue That While DKT Is A Powerful, Useful, General-purpose Framework For Modeling Student Learning, Its Gains Do Not Come From The Discovery Of Novel Representations--the Fundamental Advantage Of Deep Learning. To Answer The Question Posed In Our Title, Knowledge Tracing May Be A Domain That Does "not" Require 'depth'; Shallow Models Like BKT Can Perform Just As Well And Offer Us Greater Interpretability And Explanatory Power. [For The Full Proceedings, See ED592609.]

By

In theoretical cognitive science, there is a tension between highly structured models whose parameters have a direct psychological interpretation and highly complex, general-purpose models whose parameters and representations are difficult to interpret. The former typically provide more insight into cognition but the latter often perform better. This tension has recently surfaced in the realm of educational data mining, where a deep learning approach to predicting students' performance as they work through a series of exercises--termed "deep knowledge tracing" or "DKT"--has demonstrated a stunning performance advantage over the mainstay of the field, "Bayesian knowledge tracing" or "BKT." In this article, we attempt to understand the basis for DKT's advantage by considering the sources of statistical regularity in the data that DKT can leverage but which BKT cannot. We hypothesize four forms of regularity that BKT fails to exploit: recency effects, the contextualized trial sequence, inter-skill similarity, and individual variation in ability. We demonstrate that when BKT is extended to allow it more flexibility in modeling statistical regularities--using extensions previously proposed in the literature--BKT achieves a level of performance indistinguishable from that of DKT. We argue that while DKT is a powerful, useful, general-purpose framework for modeling student learning, its gains do not come from the discovery of novel representations--the fundamental advantage of deep learning. To answer the question posed in our title, knowledge tracing may be a domain that does "not" require 'depth'; shallow models like BKT can perform just as well and offer us greater interpretability and explanatory power. [For the full proceedings, see ED592609.]

“ERIC ED592694: How Deep Is Knowledge Tracing? In Theoretical Cognitive Science, There Is A Tension Between Highly Structured Models Whose Parameters Have A Direct Psychological Interpretation And Highly Complex, General-purpose Models Whose Parameters And Representations Are Difficult To Interpret. The Former Typically Provide More Insight Into Cognition But The Latter Often Perform Better. This Tension Has Recently Surfaced In The Realm Of Educational Data Mining, Where A Deep Learning Approach To Predicting Students' Performance As They Work Through A Series Of Exercises--termed "deep Knowledge Tracing" Or "DKT"--has Demonstrated A Stunning Performance Advantage Over The Mainstay Of The Field, "Bayesian Knowledge Tracing" Or "BKT." In This Article, We Attempt To Understand The Basis For DKT's Advantage By Considering The Sources Of Statistical Regularity In The Data That DKT Can Leverage But Which BKT Cannot. We Hypothesize Four Forms Of Regularity That BKT Fails To Exploit: Recency Effects, The Contextualized Trial Sequence, Inter-skill Similarity, And Individual Variation In Ability. We Demonstrate That When BKT Is Extended To Allow It More Flexibility In Modeling Statistical Regularities--using Extensions Previously Proposed In The Literature--BKT Achieves A Level Of Performance Indistinguishable From That Of DKT. We Argue That While DKT Is A Powerful, Useful, General-purpose Framework For Modeling Student Learning, Its Gains Do Not Come From The Discovery Of Novel Representations--the Fundamental Advantage Of Deep Learning. To Answer The Question Posed In Our Title, Knowledge Tracing May Be A Domain That Does "not" Require 'depth'; Shallow Models Like BKT Can Perform Just As Well And Offer Us Greater Interpretability And Explanatory Power. [For The Full Proceedings, See ED592609.]” Metadata:

  • Title: ➤  ERIC ED592694: How Deep Is Knowledge Tracing? In Theoretical Cognitive Science, There Is A Tension Between Highly Structured Models Whose Parameters Have A Direct Psychological Interpretation And Highly Complex, General-purpose Models Whose Parameters And Representations Are Difficult To Interpret. The Former Typically Provide More Insight Into Cognition But The Latter Often Perform Better. This Tension Has Recently Surfaced In The Realm Of Educational Data Mining, Where A Deep Learning Approach To Predicting Students' Performance As They Work Through A Series Of Exercises--termed "deep Knowledge Tracing" Or "DKT"--has Demonstrated A Stunning Performance Advantage Over The Mainstay Of The Field, "Bayesian Knowledge Tracing" Or "BKT." In This Article, We Attempt To Understand The Basis For DKT's Advantage By Considering The Sources Of Statistical Regularity In The Data That DKT Can Leverage But Which BKT Cannot. We Hypothesize Four Forms Of Regularity That BKT Fails To Exploit: Recency Effects, The Contextualized Trial Sequence, Inter-skill Similarity, And Individual Variation In Ability. We Demonstrate That When BKT Is Extended To Allow It More Flexibility In Modeling Statistical Regularities--using Extensions Previously Proposed In The Literature--BKT Achieves A Level Of Performance Indistinguishable From That Of DKT. We Argue That While DKT Is A Powerful, Useful, General-purpose Framework For Modeling Student Learning, Its Gains Do Not Come From The Discovery Of Novel Representations--the Fundamental Advantage Of Deep Learning. To Answer The Question Posed In Our Title, Knowledge Tracing May Be A Domain That Does "not" Require 'depth'; Shallow Models Like BKT Can Perform Just As Well And Offer Us Greater Interpretability And Explanatory Power. [For The Full Proceedings, See ED592609.]
  • Author:
  • Language: English

“ERIC ED592694: How Deep Is Knowledge Tracing? In Theoretical Cognitive Science, There Is A Tension Between Highly Structured Models Whose Parameters Have A Direct Psychological Interpretation And Highly Complex, General-purpose Models Whose Parameters And Representations Are Difficult To Interpret. The Former Typically Provide More Insight Into Cognition But The Latter Often Perform Better. This Tension Has Recently Surfaced In The Realm Of Educational Data Mining, Where A Deep Learning Approach To Predicting Students' Performance As They Work Through A Series Of Exercises--termed "deep Knowledge Tracing" Or "DKT"--has Demonstrated A Stunning Performance Advantage Over The Mainstay Of The Field, "Bayesian Knowledge Tracing" Or "BKT." In This Article, We Attempt To Understand The Basis For DKT's Advantage By Considering The Sources Of Statistical Regularity In The Data That DKT Can Leverage But Which BKT Cannot. We Hypothesize Four Forms Of Regularity That BKT Fails To Exploit: Recency Effects, The Contextualized Trial Sequence, Inter-skill Similarity, And Individual Variation In Ability. We Demonstrate That When BKT Is Extended To Allow It More Flexibility In Modeling Statistical Regularities--using Extensions Previously Proposed In The Literature--BKT Achieves A Level Of Performance Indistinguishable From That Of DKT. We Argue That While DKT Is A Powerful, Useful, General-purpose Framework For Modeling Student Learning, Its Gains Do Not Come From The Discovery Of Novel Representations--the Fundamental Advantage Of Deep Learning. To Answer The Question Posed In Our Title, Knowledge Tracing May Be A Domain That Does "not" Require 'depth'; Shallow Models Like BKT Can Perform Just As Well And Offer Us Greater Interpretability And Explanatory Power. [For The Full Proceedings, See ED592609.]” Subjects and Themes:

Edition Identifiers:

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The book is available for download in "texts" format, the size of the file-s is: 10.02 Mbs, the file-s for this book were downloaded 56 times, the file-s went public at Fri Jul 22 2022.

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Find ERIC ED592694: How Deep Is Knowledge Tracing? In Theoretical Cognitive Science, There Is A Tension Between Highly Structured Models Whose Parameters Have A Direct Psychological Interpretation And Highly Complex, General-purpose Models Whose Parameters And Representations Are Difficult To Interpret. The Former Typically Provide More Insight Into Cognition But The Latter Often Perform Better. This Tension Has Recently Surfaced In The Realm Of Educational Data Mining, Where A Deep Learning Approach To Predicting Students' Performance As They Work Through A Series Of Exercises--termed "deep Knowledge Tracing" Or "DKT"--has Demonstrated A Stunning Performance Advantage Over The Mainstay Of The Field, "Bayesian Knowledge Tracing" Or "BKT." In This Article, We Attempt To Understand The Basis For DKT's Advantage By Considering The Sources Of Statistical Regularity In The Data That DKT Can Leverage But Which BKT Cannot. We Hypothesize Four Forms Of Regularity That BKT Fails To Exploit: Recency Effects, The Contextualized Trial Sequence, Inter-skill Similarity, And Individual Variation In Ability. We Demonstrate That When BKT Is Extended To Allow It More Flexibility In Modeling Statistical Regularities--using Extensions Previously Proposed In The Literature--BKT Achieves A Level Of Performance Indistinguishable From That Of DKT. We Argue That While DKT Is A Powerful, Useful, General-purpose Framework For Modeling Student Learning, Its Gains Do Not Come From The Discovery Of Novel Representations--the Fundamental Advantage Of Deep Learning. To Answer The Question Posed In Our Title, Knowledge Tracing May Be A Domain That Does "not" Require 'depth'; Shallow Models Like BKT Can Perform Just As Well And Offer Us Greater Interpretability And Explanatory Power. [For The Full Proceedings, See ED592609.] at online marketplaces:


3ERIC ED610593: The Effect Of Using Hendy's 4Cs Model On Teaching And Learning Science In Middle School In Mid-Egypt Educational Research And Practice Have Proven That There Are Many Benefits For Applying Learning Theories' Recommendations Through Teaching And Learning Of Different Subjects In All School Levels. Based On Interrelationships Among Learning Theories Of Contextualism, Connectivism, Constructivism, And Cognitivism, The Researcher Proposed An Instructional Model Under The Title Of 4Cs Model: Contextualizing, Connecting, Constructing, And Cognitivizing To Take The Learner Through A Mental Trip From Observing And Examining Real Materials To Long-term Memory. However, The Main Purpose Of This Study Was To Identify The Effect Of Using The Proposed Model On Acquiring Some Scientific Concepts, Life Skills, And Multiple Intelligences Of Middle School Female Students. To Investigate This Main Purpose, Three Research Statistical Hypotheses Were Set Regarding The Three Dependent Variables. The Study Population Was The Second Grade Female Students In Middle School In Mid-Egypt. A Random Sample (72 Students) Was Chosen And Divided Into Two Groups: An Experimental Group (37) And A Control Group (35).Three Research Instruments; Achievement Test, Life Skills Scale, And Multiple Intelligences Test Were Developed And Controlled In Respect To Validity And Reliability. After Conducting The Research Experiment Using The Quasi-experimental Design, Administering Instruments, And Analyzing Data, The Results Explored That There Is An Impact For The 4Cs Model On Acquiring Scientific Concepts, Life Skills, And Multiple Intelligence Of Middle School Female Students.

By

Educational research and practice have proven that there are many benefits for applying learning theories' recommendations through teaching and learning of different subjects in all school levels. Based on interrelationships among learning theories of contextualism, connectivism, constructivism, and cognitivism, the researcher proposed an instructional model under the title of 4Cs model: contextualizing, connecting, constructing, and cognitivizing to take the learner through a mental trip from observing and examining real materials to long-term memory. However, the main purpose of this study was to identify the effect of using the proposed model on acquiring some scientific concepts, life skills, and multiple intelligences of middle school female students. To investigate this main purpose, three research statistical hypotheses were set regarding the three dependent variables. The study population was the second grade female students in middle school in Mid-Egypt. A random sample (72 students) was chosen and divided into two groups: an experimental group (37) and a control group (35).Three research instruments; achievement test, life skills scale, and multiple intelligences test were developed and controlled in respect to validity and reliability. After conducting the research experiment using the quasi-experimental design, administering instruments, and analyzing data, the results explored that there is an impact for the 4Cs model on acquiring scientific concepts, life skills, and multiple intelligence of middle school female students.

“ERIC ED610593: The Effect Of Using Hendy's 4Cs Model On Teaching And Learning Science In Middle School In Mid-Egypt Educational Research And Practice Have Proven That There Are Many Benefits For Applying Learning Theories' Recommendations Through Teaching And Learning Of Different Subjects In All School Levels. Based On Interrelationships Among Learning Theories Of Contextualism, Connectivism, Constructivism, And Cognitivism, The Researcher Proposed An Instructional Model Under The Title Of 4Cs Model: Contextualizing, Connecting, Constructing, And Cognitivizing To Take The Learner Through A Mental Trip From Observing And Examining Real Materials To Long-term Memory. However, The Main Purpose Of This Study Was To Identify The Effect Of Using The Proposed Model On Acquiring Some Scientific Concepts, Life Skills, And Multiple Intelligences Of Middle School Female Students. To Investigate This Main Purpose, Three Research Statistical Hypotheses Were Set Regarding The Three Dependent Variables. The Study Population Was The Second Grade Female Students In Middle School In Mid-Egypt. A Random Sample (72 Students) Was Chosen And Divided Into Two Groups: An Experimental Group (37) And A Control Group (35).Three Research Instruments; Achievement Test, Life Skills Scale, And Multiple Intelligences Test Were Developed And Controlled In Respect To Validity And Reliability. After Conducting The Research Experiment Using The Quasi-experimental Design, Administering Instruments, And Analyzing Data, The Results Explored That There Is An Impact For The 4Cs Model On Acquiring Scientific Concepts, Life Skills, And Multiple Intelligence Of Middle School Female Students.” Metadata:

  • Title: ➤  ERIC ED610593: The Effect Of Using Hendy's 4Cs Model On Teaching And Learning Science In Middle School In Mid-Egypt Educational Research And Practice Have Proven That There Are Many Benefits For Applying Learning Theories' Recommendations Through Teaching And Learning Of Different Subjects In All School Levels. Based On Interrelationships Among Learning Theories Of Contextualism, Connectivism, Constructivism, And Cognitivism, The Researcher Proposed An Instructional Model Under The Title Of 4Cs Model: Contextualizing, Connecting, Constructing, And Cognitivizing To Take The Learner Through A Mental Trip From Observing And Examining Real Materials To Long-term Memory. However, The Main Purpose Of This Study Was To Identify The Effect Of Using The Proposed Model On Acquiring Some Scientific Concepts, Life Skills, And Multiple Intelligences Of Middle School Female Students. To Investigate This Main Purpose, Three Research Statistical Hypotheses Were Set Regarding The Three Dependent Variables. The Study Population Was The Second Grade Female Students In Middle School In Mid-Egypt. A Random Sample (72 Students) Was Chosen And Divided Into Two Groups: An Experimental Group (37) And A Control Group (35).Three Research Instruments; Achievement Test, Life Skills Scale, And Multiple Intelligences Test Were Developed And Controlled In Respect To Validity And Reliability. After Conducting The Research Experiment Using The Quasi-experimental Design, Administering Instruments, And Analyzing Data, The Results Explored That There Is An Impact For The 4Cs Model On Acquiring Scientific Concepts, Life Skills, And Multiple Intelligence Of Middle School Female Students.
  • Author:
  • Language: English

“ERIC ED610593: The Effect Of Using Hendy's 4Cs Model On Teaching And Learning Science In Middle School In Mid-Egypt Educational Research And Practice Have Proven That There Are Many Benefits For Applying Learning Theories' Recommendations Through Teaching And Learning Of Different Subjects In All School Levels. Based On Interrelationships Among Learning Theories Of Contextualism, Connectivism, Constructivism, And Cognitivism, The Researcher Proposed An Instructional Model Under The Title Of 4Cs Model: Contextualizing, Connecting, Constructing, And Cognitivizing To Take The Learner Through A Mental Trip From Observing And Examining Real Materials To Long-term Memory. However, The Main Purpose Of This Study Was To Identify The Effect Of Using The Proposed Model On Acquiring Some Scientific Concepts, Life Skills, And Multiple Intelligences Of Middle School Female Students. To Investigate This Main Purpose, Three Research Statistical Hypotheses Were Set Regarding The Three Dependent Variables. The Study Population Was The Second Grade Female Students In Middle School In Mid-Egypt. A Random Sample (72 Students) Was Chosen And Divided Into Two Groups: An Experimental Group (37) And A Control Group (35).Three Research Instruments; Achievement Test, Life Skills Scale, And Multiple Intelligences Test Were Developed And Controlled In Respect To Validity And Reliability. After Conducting The Research Experiment Using The Quasi-experimental Design, Administering Instruments, And Analyzing Data, The Results Explored That There Is An Impact For The 4Cs Model On Acquiring Scientific Concepts, Life Skills, And Multiple Intelligence Of Middle School Female Students.” Subjects and Themes:

Edition Identifiers:

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The book is available for download in "texts" format, the size of the file-s is: 8.89 Mbs, the file-s for this book were downloaded 41 times, the file-s went public at Thu Jul 14 2022.

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Archive BitTorrent - DjVuTXT - Djvu XML - Item Tile - Metadata - OCR Page Index - OCR Search Text - Page Numbers JSON - Scandata - Single Page Processed JP2 ZIP - Text PDF - chOCR - hOCR -

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Find ERIC ED610593: The Effect Of Using Hendy's 4Cs Model On Teaching And Learning Science In Middle School In Mid-Egypt Educational Research And Practice Have Proven That There Are Many Benefits For Applying Learning Theories' Recommendations Through Teaching And Learning Of Different Subjects In All School Levels. Based On Interrelationships Among Learning Theories Of Contextualism, Connectivism, Constructivism, And Cognitivism, The Researcher Proposed An Instructional Model Under The Title Of 4Cs Model: Contextualizing, Connecting, Constructing, And Cognitivizing To Take The Learner Through A Mental Trip From Observing And Examining Real Materials To Long-term Memory. However, The Main Purpose Of This Study Was To Identify The Effect Of Using The Proposed Model On Acquiring Some Scientific Concepts, Life Skills, And Multiple Intelligences Of Middle School Female Students. To Investigate This Main Purpose, Three Research Statistical Hypotheses Were Set Regarding The Three Dependent Variables. The Study Population Was The Second Grade Female Students In Middle School In Mid-Egypt. A Random Sample (72 Students) Was Chosen And Divided Into Two Groups: An Experimental Group (37) And A Control Group (35).Three Research Instruments; Achievement Test, Life Skills Scale, And Multiple Intelligences Test Were Developed And Controlled In Respect To Validity And Reliability. After Conducting The Research Experiment Using The Quasi-experimental Design, Administering Instruments, And Analyzing Data, The Results Explored That There Is An Impact For The 4Cs Model On Acquiring Scientific Concepts, Life Skills, And Multiple Intelligence Of Middle School Female Students. at online marketplaces:


4Statistical Learning And Data Science

Educational research and practice have proven that there are many benefits for applying learning theories' recommendations through teaching and learning of different subjects in all school levels. Based on interrelationships among learning theories of contextualism, connectivism, constructivism, and cognitivism, the researcher proposed an instructional model under the title of 4Cs model: contextualizing, connecting, constructing, and cognitivizing to take the learner through a mental trip from observing and examining real materials to long-term memory. However, the main purpose of this study was to identify the effect of using the proposed model on acquiring some scientific concepts, life skills, and multiple intelligences of middle school female students. To investigate this main purpose, three research statistical hypotheses were set regarding the three dependent variables. The study population was the second grade female students in middle school in Mid-Egypt. A random sample (72 students) was chosen and divided into two groups: an experimental group (37) and a control group (35).Three research instruments; achievement test, life skills scale, and multiple intelligences test were developed and controlled in respect to validity and reliability. After conducting the research experiment using the quasi-experimental design, administering instruments, and analyzing data, the results explored that there is an impact for the 4Cs model on acquiring scientific concepts, life skills, and multiple intelligence of middle school female students.

“Statistical Learning And Data Science” Metadata:

  • Title: ➤  Statistical Learning And Data Science
  • Language: English

“Statistical Learning And Data Science” Subjects and Themes:

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