Application of invented algorithm to organize and use algorithm in teaching genetics (Biology 12 - High School) to develop cognitive capacity and creative thinking capacity for students.
THAI NGUYEN UNIVERSITY UNIVERSITY OF EDUCATION TRUONG MONG DIEN THE APPLICATION OF INVENTED ALGORITHM IN ORGANIZING GENETICS TEACHING (GRADE 12 – BIOLOGY PROGRAM) Specialty: Theory and Methodology of Biology Teaching Code: 9140111 DISERTATION SUMMARY THAI NGUYEN 2020 The dissertation was completed at THAI NGUYEN UNIVERSITY – UNIVERSITY OF EDUCATION Supervisors: Assoc. Prof. PhD. Nguyen Phuc Chinh Reviewer 1: Reviewer 2: Reviewer 3: The dissertation will be defended in the university committee: THAI NGUYEN UNIVERSITY – UNIVERSITY OF EDUCATION At h on ……………. 2020 The dissertation can be found at: National library of Vietnam’ Thai Nguyen University Learning Resource Center; Library ò University of Education Thư viện Trường Đại học Sư phạm Thái Nguyên PUBLISHED WORKS RELATED TO THE DISSERTATION Nguyen Phuc Chinh, Truong Mong Dien (2013), "Overview of Invented Algorithm, Journal of Science and Technology, Thai Nguyen University, No. 14, p. 211215 Truong Mong Dien, Nguyen Phuc Chinh (2015), "Scientific basis of applying Invented Algorithm in teaching", Journal of Education, No. 361, issue 1 in July 2015, p.1618 Truong Mong Dien (2016), "The use of Algorithm method in teaching Biology", Journal of Education, No. 375, issue 1 on February 2016, p.5557 INTRODUCTION 1. Rationate It is derived from the need to innovate teaching methods, the advantages of invented algorithm, the characteristics of genetic knowledge (Biology 12), the dissertation title of “The application of invented algorithm in organizing Genetics teaching (Grade 12 Biology Program)” has been chosen 2. Objectives of the study Application of invented algorithm to organize and use algorithm in teaching genetics (Biology 12 High School) to develop cognitive capacity and creative thinking capacity for students 3. Research subject and object Research subject: Teaching Genetics (Biology 12 High School) according to the invented algorithm Research object: Teaching process of Biology 12 High School 4. Scientific hypothesis If algorithm is built and used appropriately in the stages of teaching Genetics (Biology 12 High School), it will develop cognitive and creative thinking capacity for students 5. Limitations of the dissertation title The dissertation researches and applies invented algorithm theory in teaching Genetics (Biology 12 High School) 6. Research mission (1) Research of invented algorithmic theory and application of algorithm in teaching (2) Investigation of the situation of algorithmic application in teaching process in high schools (3) Proposing the process of developing some algorithms in teaching Genetics (Biology 12 High School) (4) Developing a process of using algorithm which is built in teaching Genetics (Biology 12 High School) (5) Pedagogical experiment to evaluate the effectiveness of the proposed options 7. Research Methods Method of theoretical research, Method of pedagogical investigation, Method of experts, Method of consultation with experts, Method of pedagogical experiment 8. New contributions of the dissertation (1) Proposing the process of developing some algorithms for teaching Genetics (Biology 12 High School) (2) Proposing the process of using some algorithms in teaching Genetics (Biology 12 High School) (3) Proposing a scale to evaluate the efficiency of applying invented algorithm in teaching Genetics (Biology 12 High school) 9. The structure of the dissertation In addition to the introduction, conclusions, references and appendices, the main content of the dissertation is presented in three chapters: Chapter Theoretical and practical basis Chapter 2. Application of invented algorithm in teaching Genetics (Biology 12 High School). Chapter 3. Pedagogical experiment Chapter 1: THEORETICAL AND PRACTICAL BASIS 1.1. Research history of algorithm 1.1.1. History of algorithmic research in the world Science of Creativity in the world has been formed for a long time The Greek mathematician, Pappop, founded the “Science of Creativity”, which he named Heuristics Alfred Binet is a French psychologist who invented the first practical IQ test In 1939, A. Osborn (American) proposed a method of brain stimulation or brainstorming In 1926, F Kunze proposed the target audience method. In 1942, the method of morphological analysis was proposed by the Swiss. It was developed by Fritz Zwicky. The person who has made a lot of contributions to developing innovative science is Genric Sanlovic AltshulerAnthony. "Tony" Peter Buzan is the father of the Mind map method. In 1983, a professor of psychology called Howard Gardner of Harvard University published the theory of " Multiple Intelligences". In 1992, Habits of Mind was introduced by PhD Arthur Costa, Honorary Professor at California State University. Today, the research works of thought and creativity have been given appropriate attention and have brought high efficiency in many fields in many countries around the world 1.1.2. History of algorithmic research in Vietnam The person who has brought Science of Creativity into Vietnam is Prof Phan Dung with works such as: Scientific and technical innovation methodology of problem solving and decision making; Basic creative principles; The world inside creative human beings… In 1991, Center for Scientific and Technical Creativity was established at the University of Science Viet Nam National University, Ho Chi Minh City with the purpose of teaching ordinary people to be creative. In 1998, Mr Nguyen Van Le and his work “The Scientific Basis of Creativity” presented a number of scientific foundations of educating creativity for young people. Nguyen Minh Triet with “Awakening of Creative Potential” in 2000 and Nguyen Canh Toan with “Initiating of Creative Potential” in 2004 brought up issues of creative learning 1.2. Theoretical Basis 1.2.1. Some basic concepts 1.2.1.1. Algorithm: 1.2.1.2. Invented algorithm: 1.2.1.3. Theory for solving invented problems 1.2.2. Classification of Algorithm 1.2.2.1. Recognition algorithm It is the Algorithm that results in the judgment of type x of A x: perceived object. A: some kind. 1.2.2.2. Transform algorithm All Algorithms that are not Recognition algorithm belong to transform algorithm. 1.2.3. The role of algorithm in teaching in general and in teaching Genetics in particular 1.2.3.1. The role of algorithm in teaching For students Firstly, the first benefit that algorithmic method brings is to help students formulate 3 problem solving methods in an algorithmic manner. Secondly, the algorithmic method helps to promote students' positive and oriented thinking Thirdly, it forms a common and general method of scientific thinking and purposeful activities For teachers Firstly, teaching by algorithmic methods helps teachers formulate methods to solve problems for students in a focused, quick and effective manner. Secondly, it helps teachers develop teaching algorithms systematically and effectively. Thanks to the algorithms, students will acquire knowledge better. Thirdly, it also helps teachers design well the content of “customized teaching program” to help students acquire the knowledge that teachers impart in a best way and most systematically 1.2.3.2. The role of algorithm in teaching Genetics The role of algorithm in teaching Genetics is to provide the right solution, avoid confused situation and having no advance orientation. From an exercise or an example of a teacher, students can apply to a variety of similar exercises. The second role is to help students work systematically, know how to use visual images to make the problem clear, easy to understand and avoid confusion when solving them. The last one is to help students know how to exploit and use problematic data in a rational way For excellent students: the algorithm helps students get fast, accurate results, which takes less time, so that they can think of other solution methods. For weak students: Following the steps correctly in the algorithm record will help students find the correct solution, this helps them to have confidence in learning, to be encouraged and encouraged, which will form a better sense of learning. 1.2.4. Scientific basis of applying algorithm in teaching 1.2.4.1. Mathematical basis algorithmic theory The mathematical basis of the algorithm defines Finality; Determinability; Universality; I/O Quantity; The effectiveness of the algorithm 1.2.4.2. Basis of creative psychology By analyzing the creative principles of G. Altshuller, we found that there are 8 creative principles that can be applied in teaching, namely: The principle of division; Principle of association; Principle of local quality; Principle of changing physical and chemical parameters; Principles of using intermediaries; Reversal principle; Principle of flexibility and Principle of impact on "noise" 1.2.4.3. Basis of information theory Algorithm has the effect of modeling research objects and coding them with a kind of "language" that is both intuitive and specific Therefore, teaching by algorithm makes the process of information transmission faster and more accurate 1.2.4.4. Basis of control theory Application of invented algorithm in the teaching process will enhance the inverse relationship between teachers and students because the invented algorithm promotes students' creative thinking, independence and autonomy 1.2.4.5. The basis of cognitive psychology and psychology at different ages 1.3. Practical basis 1.3.1. Actual awareness of teachers' reasoning Investigation of the theoretical cognitive status of teachers includes perceptions of concepts, roles, algorithmic classification of teachers in high schools today 1.3.2. Practices of using algorithm of teachers in teaching Genetics Practical investigations of algorithmic use include the extent, benefits and difficulties of using algorithm of teacher The results show that teaching with the use of algorithm is rarely applied by teachers, and if it is applied, it will only be used in a very small amount of content in certain stages of teaching. Teachers still have many confusion and difficulties when teaching algorithms, so algorithm teaching has not been widely implemented and conducted regularly Teachers often use existing processes, the design of algorithms appropriate to the teacher's targets and subjects of teaching is still limited Chapter 2. APPLICATION OF INVENTED ALGORITHM IN TEACHING GENETICS (BIOLOGY 12 HIGH SCHOOL) 2.1. Analysis of structure and content of Genetics part (Biology 12 High School) In order to apply the algorithm in teaching genetics properly and effectively, we have conducted the content analysis of each chapter in genetics part to determine the content that can apply algorithms and apply them in theoretical teaching or genetic exercises. 2.2 Developing algorithm for teaching Genetics (Biology 12 High School) 2.2.1 Principles of developing algorithm for teaching Genetics (Biology 12 High School) 2.2.1.1. Conformity with the program objectives and content 2.2.1.2. Guarantee of unity between science and education 2.2.1.3. User friendly 2.2.2. Process of developing algorithm for teaching Genetics part (Biology 12) 2.2.2.1. Process of developing recognition algorithm Process of developing Step 1: Determination of knowledge target Step 2: Description algorithmic content recognition algorithm Step 3: Preparation of algorithmic records Step 4: Algorithm is active Figure 2.2. Process of developing recognition algorithm Example: Developing recognition algorithm for Mendelian inheritance Step 1: Determination of knowledge target Students: Present the essential signs of Mendel's laws of inheritance; Identify the Mendel's laws of inheritance in genetic exercises Step 2: Description algorithmic content Inherited by strict rules The result of two factor cross is the same Mendelian inheritance The characteristic is equally expressed in both sexes Each pair of genes specifies a pair of characters Each pair of genes lies on a different homologous chromosome Complete dominant recessive 12 From the genetic characteristics of the sex linkage genetic rule, the teacher will introduce students the algorithmic records identifying the sex linkage genetic rule that have been designed by the teacher W The expression characters are irregular in both sexes It is not sex linkage rule R Same Result of twoway cross Genes are located in the homologous regions of X and Y Different The character appears only in heterogametic sex W R Genes on the Y chromosome in the part that do not have homologous regions on the X chromosome (crossed inheritance) Genes on the X chromosome in the part that do not have homologous regions on the Y chromosome (direct inheritance) Teacher: The instructions for using the algorithmic record to identify the sex linkage genetic rule are as follows: (1) The expression characters are irregular in both sexes. If the result is wrong, it is concluded that it is not sex linkage genetic rule. If it is right, go to step 2 or skip step 2 to go straight to step 3 (2) Result of twoway cross: If result of twoway cross is the same, it is concluded that the expression characters is by the gene located on the homologous region of the X and Y chromosomes. If result of twoway cross is different, go to step 3 (3) The character appears only in heterogametic sex (having XY chromosomes). If the result is right, it is concluded that it is due to genes on the Y chromosome in the part that not have homologous regions on the X chromosome (direct inheritance). If it is wrong, the conclusion is it is due to genes on the X chromosome in the part that do not have homologous regions on the Y chromosome (crossed inheritance) 13 Step 4: Practice and apply them The teacher asks students to come back to Morgan’s experiment to practice using algorithmic records Students perform the request of the teacher individually Expression characters are irregular in both sexes: Right → It is sex linkage genetic character Result of twoway cross is different: Right The character appears in both sexes → The character is due to X chromosome gene in the part that do not have homologous allele on the Y chromosome Teacher assigns other exercise: Exercise: Suppose a striped rooster breeds with a blackfurred hen and all of their offspring (F1) is striped chickens Next, F1 continue to breed with F1, F2 includes 50 striped chickens and 16 blackfurred chickens and all blackfurred chickens are hens. Which rule is fur color characters inherited? Teachers ask students to discuss in groups to do the exercise or also assign home tasks for students Illustrative example Developing recognition algorithms for nuclear inheritance rule Step 1: Determine the target Students need to identify targets: distinguish the nuclear inheritance rule Step 2: Organize students to analyze logical knowledge To organize students to analyze knowledge logic about nuclear inheritance rule, teachers can navigate by a system of questions such as: What factors govern nuclear inheritance rule? Which nuclear inheritance rule have you learned? What is the relationship between these genetic laws? Students mobilize the learned knowledge to answer the suggested questions of teachers and find out the knowledge logic: Step 3: Students develop their own algorithmic records To organize students to design their own algorithmic records to recognize the nuclear inheritance rule, teachers can guide students: (1) List the identifying signs of each genetic rule (2) Arrange individual signs to identify each rule 14 Teachers can suggest students complete the following table: Identifying signs Character The number of expression in gene pairs per both sexes chromosome Rule Twoway cross The number of genes pairs of a pair of characters Menden Gene interaction Genetic linkage Sex linkage (3) Algorithmic preliminary design algorithm Students can use pencil to sketch out the algorithm on paper. Put the nature signs in order, draw arrows and find instructions to draw (4) Inspection and completion 2.3.2.2. Using algorithms in teaching Genetics exercises Step 1: Teacher selects exercises and assigns tasks Step 1: Teacher selects exercises and assigns tasks Stage 1 Stage 1 Step 2: Organize students establish the relationship between Step 2: Organize students establish the relationship between hypothesis and conclusion hypothesis and conclusion Use algorithm to Use algorithm to guide students to guide students to solve genetic solve genetic exercises exercises Step 3: Teacher provides problem solving program Step 3: Teacher provides problem solving program Step 4: Students solve problems according to the program Step 4: Students solve problems according to the program Step 5: Practice Step 5: Practice Step 1: Teacher selects exercises and assigns tasks Step 1: Teacher selects exercises and assigns tasks Stage 2 Stage 2 Instruct students to Instruct students to develop their own develop their own algorithm for solving algorithm for solving genetic exercises genetic exercises Step 2: Organize students establish the relationship between Step 2: Organize students establish the relationship between hypothesis and conclusion hypothesis and conclusion Step 3: Organize students to develop their own problem solving Step 3: Organize students to develop their own problem solving program program Step 4: Comment and complete the problem solving program Step 4: Comment and complete the problem solving program Stage 3 Stage 3 Apply creative Apply creative principles to principles to develop and develop and solve creative solve creative exercises exercises Level 1: Teacher Level 1: Teacher s develop s develop creative creative exercises for exercises for students to students to practice practice Step 1: Select problem Step 1: Select problem Step 2: Identify and solve problems Step 2: Identify and solve problems Step 3: Teachers introduce creative exercises based Step 3: Teachers introduce creative exercises based on creative principles on creative principles Step 4: Develop solving programs and solve Step 4: Develop solving programs and solve creative exercises creative exercises Step 5: Practice Step 5: Practice Level 2: Level 2: Teachers guide Teachers guide students to students to develop develop creative creative exercises exercises Step 1: Select problem Step 1: Select problem Step 2: Solve problems Step 2: Solve problems Step 3: Organize students to develop their own Step 3: Organize students to develop their own creative exercises based on creative principles creative exercises based on creative principles Step 4: Students develop a program to solve the Step 4: Students develop a program to solve the problem exercises problem exercises Step 5: Comment and conclude Step 5: Comment and conclude 15 Stage 1: Use algorithm to guide students to solve genetic exercises Step 1: Teacher selects exercises and assigns tasks Based on the targets of knowledge, skills, competencies to be achieved and based on the cognitive capacity of each student class, teachers choose appropriate exercises Step 2: Organize students establish the relationship between hypothesis and conclusion The establishment of the relationship between the hypothesis and the conclusions is that the students analyze the problem to mobilize known knowledge, identify the requirements and think about how to solve the problem Step 3: Teacher provides problem solving program In stage 1, teachers need to develop sample programs for students to familiarize themselves with the learning method and to learn how to build the next learning program Step 4: Students solve problems according to the program For students with average and weak study ability, they will be more confident and more interested in learning than when they solve problems after being provided with solving programs, from which they will love the subject more With good students, this can be considered as a stepping stone for them to accumulate more knowledge and experience to prepare for designing their own learning programs according to algorithm Stage 2: Instruct students to develop their own algorithm for solving genetic exercises Step 1, step 2 of this stage is basically the same as stage 1 Step 3: Organize students to develop their own problem solving program In this step, when students design the algorithm themselves, the algorithms are the product of students' thinking process. Students 16 think, write and draw by their own language, thus maximizing the potential of the brain. On the other hand, due to being selfcreated, it creates interest in learning for students This method first helps students understand the lesson and memorize the lesson better, and then train them to think logically and coherently so that they know how to solve problems scientifically in other situations. This is the target of using algorithm in teaching to be achieved Step 4: Comment and complete the problem solving program Teachers organize for students to report their results and lessons learned. Teachers synthesize ideas, then standardize to help students perfect the problem solving program. In this step, teachers can also motivate students to think by asking them to generalize the exercises into a general form Stage 3: Apply creative principles to develop and solve creative exercises Level 1: Teachers develop creative exercises for students to practice Step 1: Select problem The selection of problems in this period is similar to the above two stages Teachers also need to pay attention to the lesson objectives, student level to choose the problem accordingly Step 2: Identify and solve problems The problem selected in step is the starting problem. Teachers organize students to identify genetics part that problem belongs to Step 3: Teachers introduce creative exercises based on creative principles When giving creative exercises, teachers should clearly state how the exercises are created and the creative principles on which the exercises are based so that students can easily visualize and think Step 4: Develop solving programs and solve creative exercises Level 2: Teachers guide students to develop creative exercises 17 Basically, step 1 and step 2 in level 2 are the same as step 1 and step 2 in stage 1 Step 3: Organize students to develop their own creative exercises Based on the creative cycle of Razumovsky [35], based on the system of creative principles, the development of creative exercises in the dissertation is conducted as follows: Starting problem Concepts and rules Develop methods to solve problems and find results Make questions and answers Creative principles Creative problem 2.3.2.3. Using algorithms to enhance creative thinking and problem solving competence for students in teaching Genetics (Biology 12 High School) In teaching Genetics, the use of algorithms to enhance creative thinking and problem solving skills is most clearly revealed in teaching genetic exercises, especially when they develop and solve creative assignments Creative exercise The process of applying creative principles to guide students in Analyze solving creative exercises takes place according to the following process: Identification Analyze Establish a relationship between hypothesis and conclusion Creative principles Propose the options Evaluate Choose the optimal plan Perform Result Comment Lesson 18 Figure 2.20. The process of solving creative exercises The level to which the creative thinking capacity and problem solving capacity in teaching is formed and developed depending on the user and the use of teaching process Using algorithm in forming new knowledge Algorithm used in teaching helps students orientate textbook research to find new knowledge, and also works to create a shortened knowledge product from textbooks. The method of using algorithms to teach new knowledge is inductive measure Using algorithm in consolidating and perfecting knowledge This is an important stage in the learner's awareness path to practice the use of the acquired knowledge in specific situations. This is to strengthen the process of acquiring knowledge, bringing knowledge to serve practical requirements, creating products similar to existing or higher, newer products This is also a period of consolidating skills to turn them into professional ones for the ultimate learning target of "Practice make perfect" Using algorithm in testing and assessing Testing and essessing is the period in which students selfassess or evaluate learning process of each other. This is also the stage for teachers to assess the level and capacity of each student, receive feedback from students to adjust the deveopment of teaching algorithms and their teaching process to suit the targets and subjects. To implement this task, teachers need to build a tool to assess the level of knowledge acquisition and level of capacity development in each student 19 Chapter 3. PEDAGOGICAL EXPERIMENT 3.1. Experimental purposes In order to check the feasibility and effectiveness of the scientific hypothesis that the subject has set; test the effectiveness of algorithms that have been developed in teaching genetics (Biology 12) 3.2. Experimental content Pedagogical experiment is conducted for a number of lessons that invented algorithm is allowed to apply to this content When applying the invented algorithm or any teaching method, we think that it must be conducted continuously and systematically to assess the effectiveness of that method in the most objective way 3.3. Experimental method 3.3.1. Selecting experimental schools, classes and teachers We conducted experiments in high schools in Hung Yen province: Before conducting the experiment, we discussed with teachers who participated in the experiment the following content: Purpose, request, task and content of conducting experiment Specific purpose, method and teaching plan for each lesson period Provide documents for teachers to participate in experimental research before experimenting. Guilding documentation includes: + Analyzing the logical structure of the content of experimental lessons + Process of 1developing algorithmic records + Process of applying algorithm to teaching genetics (Biology 12) + Methods of organizing students to apply creative principles to propose creative exercises and situations. + Sample lesson plans of genetics that apply algorithm into teaching process 3.3.2. Organization of pedagogical experiment The experiment was conducted 2 times * Phase (academic year of 2015 2016) is exploratory experiment 20 * Phase (academic year of 2016 2017) is the official experiment 3.3.3. Method of results processing 3.3.3.1. Using mathematical 1 3.3.3.2. Handling the comments of teachers and students 3.4 Criteria for assessing the effectiveness of applying invented algorithm in teaching genetics (Biology 12) 3.4.1. Assessing student's cognitive capacity Assessing the level of students' knowledge acquisition Assessing students' knowledge use ability 3.4.2 Assessing creative thinking capacity in teaching Genetics (Biology 12 High School) with applying of Algorithm 3.4.2.1 The basis for developing criteria for assessing creative capacity From these basis, we propose the following criteria to assess students' creative thinking capacity: The first criterion: From the cognitive needs of students, they can discover new problems and give dependable predictions (idea suggestion) The second criterion: From the predictions, students propose possible solutions to test the hypothesis and identify the consequences derived from the hypothesis The third criterion: Students know how to analyze the pros and cons of the proposed plans and choose the most optimal solution The fourth criterion: Students successfully implement the selected plan The fifth criterion: Identify personal experience lessons 3.4.2.2. How to evaluate Based on the above criteria, when evaluating students' creative thinking capacity, teachers need to: Design starting exercises/situations Organize students to solve the starting exercises/situations Organize students to propose creative exercises/situations and find solutions to solve those exercises/situations 21 3.4.2.3. Proposing a scale of creative thinking capacity in teaching Genetics (Biology 12 High School) 1, Problem detection Criteria Point The problem is found and dependable prediction is given 2 points The problem is found but dependable prediction is not 1 point given The problem is not found 0 point 2, The solution for solving problem has been proposed Criteria Point The solutions for solving problem and consequences of 2 solutions are proposed points The solutions for solving problem are proposed but 1 point consequences of solution is not given The solutions for solving problem are not proposed 0 point 3, Analysis and assessment of advantages and disadvantages of the solutions to choose the best option to solve the problem Criteria Point The solutions are analyzed and the most optimal option 3 points is selected The solutions are analyzed but the most optimal option is 2 points not selected The solutions are not analyzed but the most optimal 1 point option is selected The solutions are not analyzed and the most optimal 0 point option is selected 4, Successful implementation of the selected option or there are improvements compared to the selected option Criteria Point Students successfully implement the selected option and 2 propose improvement plan points Students successfully implement the selected option but 1 point improvement plan is not proposed No option is implemented 0 point 5, Lesson for each individual 22 Criteria Point Students can draw experience lessons for themselves 1 point Students cannot draw experience lessons for themselves 0 point The system of 5 criteria with the levels and scales as above can be used to measure creative thinking capacity in the teaching of genetics in particular and in teaching in general The number of points that each student obtains from the 4 above criteria is called x To evaluate students' creative thinking capacity, we divide the levels as follows: Table 3.4. Table assessing the level of creativity in the experiment Level 0 No. of point (s) 0≤ x