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Helping Students to Become Researchers: How to Propagate . . . What - PowerPoint PPT Presentation

Interval Approach: . . . Interval . . . Interval . . . Similar Situation: . . . Let Us Use a Similar . . . How to Represent Sets Helping Students to Become Researchers: How to Propagate . . . What We Can Gain from First Example: . . . How


  1. Interval Approach: . . . Interval . . . Interval . . . Similar Situation: . . . Let Us Use a Similar . . . How to Represent Sets Helping Students to Become Researchers: How to Propagate . . . What We Can Gain from First Example: . . . How to Propagate . . . Russian Experience First Example: . . . Second Example: . . . How to Compute r ik Vladik Kreinovich 1 , Olga Kosheleva 2 , Distributivity: a · ( b + . . . and Ann Gates 1 Distributivity: New . . . Toy Example with . . . 1 Department of Computer Science and Toy Example with . . . 2 Department of Teacher Education Computation Time What Next? University of Texas at El Paso, Probabilistic Case: In . . . El Paso, TX 79968, USA Acknowledgments emails vladik@utep.edu, olgak@utep.edu, When is the New . . . agates@utep.edu Title Page ◭◭ ◮◮ ◭ ◮ Page 1 of 16 Go Back

  2. Interval Approach: . . . Interval . . . 1. Synopsis Interval . . . Similar Situation: . . . • Fact: many internationally renowned scientists have been educated in the Let Us Use a Similar . . . former Soviet Union, especially in mathematics, physics, and computer sci- How to Represent Sets ence. How to Propagate . . . First Example: . . . • Reasonable conclusion: many features of the Russian education system were How to Propagate . . . good. First Example: . . . • Session objective: to (briefly) describe the features that we believe to have Second Example: . . . been good: How to Compute r ik Distributivity: a · ( b + . . . – emphasis on student groups – where students study and do research Distributivity: New . . . together, Toy Example with . . . – emphasis on working research seminars, etc. Toy Example with . . . • Some of these features have already been successfully implemented (with Computation Time appropriate adjustments) in UTEP’s affinity research groups. What Next? Probabilistic Case: In . . . Acknowledgments When is the New . . . Title Page ◭◭ ◮◮ ◭ ◮ Page 2 of 16 Go Back

  3. Interval Approach: . . . Interval . . . 2. Motivations and Clarification Interval . . . Similar Situation: . . . • Why Russian experience: two of us have been educated in Russia. Let Us Use a Similar . . . How to Represent Sets • This is not a comprehensive survey: How to Propagate . . . – we omit all the features that we we consider bad (and there were many), First Example: . . . and How to Propagate . . . First Example: . . . – our choice of useful features is (inevitably) subjective – mainly based Second Example: . . . on our own experience and on our collaboration with Prof. Nesterov How to Compute r ik (St. Petersburg, Russia). Distributivity: a · ( b + . . . We hope, nevertheless, that in spite of this subjectivity, this session will be Distributivity: New . . . useful. Toy Example with . . . • Main objective: to attract attention to (not well known) educational tech- Toy Example with . . . niques – especially since we have tried some of these techniques, and they Computation Time seem to work pretty well. What Next? Probabilistic Case: In . . . Acknowledgments When is the New . . . Title Page ◭◭ ◮◮ ◭ ◮ Page 3 of 16 Go Back

  4. Interval Approach: . . . Interval . . . 3. 3-Tier System of Students Interval . . . Similar Situation: . . . • Based on (mostly discipline-specific) tough entrance exams, accepted students Let Us Use a Similar . . . are divided into 3 tiers. How to Represent Sets How to Propagate . . . • The best students are accepted into a full-time program: First Example: . . . – state supported through stipends (kept as long a certain GPA is main- How to Propagate . . . tained); First Example: . . . – needy students and students with good GPAs get an extra stipend; Second Example: . . . – free dorms or University-mediated and -subsidized room rental; How to Compute r ik Distributivity: a · ( b + . . . – fast track. Distributivity: New . . . • Second tier: work-study students: Toy Example with . . . Toy Example with . . . – work full time; Computation Time – attend special evening classes; What Next? – take longer to graduate; Probabilistic Case: In . . . – best work-study students move to full time status. Acknowledgments • Third tier: distance learning students: When is the New . . . Title Page – receive handouts, assignments, and comments by mail, – every semester, a month-long on-campus crash course to solidify their ◭◭ ◮◮ knowledge before the finals; – take even longer to graduate. ◭ ◮ • Same material in all tiers, but employees prefer full-time (smartest) students. Page 4 of 16 Go Back

  5. Interval Approach: . . . Interval . . . 4. Clusters and Groups Interval . . . Similar Situation: . . . • Before the senior year: pre-determined sequence of classes ( clusters ), 6 hours Let Us Use a Similar . . . of classes weekday and Saturday, a lot of homework. How to Represent Sets How to Propagate . . . • After the first three years: students choose a specialization , after which they First Example: . . . get more freedom in choosing their schedules. How to Propagate . . . • Main advantage of clusters: ability to correlate different courses taken at the First Example: . . . same time. Second Example: . . . • Example: when physics and calculus are taken at the same time, mathemat- How to Compute r ik ical and physical aspects of derivatives are taught simultaneously and help Distributivity: a · ( b + . . . students relate different areas. Distributivity: New . . . Toy Example with . . . • Additional advantage of clusters: special sections of, e.g., physics tailored to- Toy Example with . . . wards CS students; this tailoring improves the understanding of the material. Computation Time • Groups: most classes are taught in two parts: What Next? – a big lecture for the entire class, and Probabilistic Case: In . . . – additional ( closed ) labs for smaller groups of students (usually, 15–20). Acknowledgments When is the New . . . To accommodate this, all the incoming full-time students are divided into Title Page groups of 15–20 students in each. • Students are assigned to the same group for all classes, exceptions: ◭◭ ◮◮ – foreign language (division by language and by mastery level); where ◭ ◮ students are divided into different groups: – physical training (by sport and by mastery). Page 5 of 16 Go Back

  6. Interval Approach: . . . Interval . . . 5. How to Divide Students into Groups Interval . . . Similar Situation: . . . • Division into groups is important: students in a group study together, help Let Us Use a Similar . . . each other. How to Represent Sets How to Propagate . . . • Result: much thought was given on how to divide students into groups. First Example: . . . • Two types of groups: How to Propagate . . . First Example: . . . – an advanced group, mostly students who graduated from a special University- Second Example: . . . supported boarding school; How to Compute r ik – other groups, to which students were distributed uniformly so that each Distributivity: a · ( b + . . . group would contain: Distributivity: New . . . ∗ approximately the same proportion of A, B, and C students, Toy Example with . . . ∗ approximately the same proportion of male and female students, Toy Example with . . . etc. Computation Time What Next? Probabilistic Case: In . . . Acknowledgments When is the New . . . Title Page ◭◭ ◮◮ ◭ ◮ Page 6 of 16 Go Back

  7. Interval Approach: . . . Interval . . . 6. Group Advisors Interval . . . Similar Situation: . . . • To each group, three advisors were assigned: Let Us Use a Similar . . . How to Represent Sets – two doctoral student advisors, and How to Propagate . . . – a faculty advisor. First Example: . . . How to Propagate . . . • Graduate student advisors: First Example: . . . – time spent: few hours per week; Second Example: . . . How to Compute r ik – duty: teach learning skills, providing advise on how to study and to relax best. Distributivity: a · ( b + . . . Distributivity: New . . . • Everyone benefits: Toy Example with . . . – advisees get help; Toy Example with . . . Computation Time – advisors loved the chance of being treated like gurus with infinite wis- What Next? dom. Probabilistic Case: In . . . • Requirement: every doctoral student is required to be an advisor, with a Acknowledgments (Pass/Fail) grade every semester. When is the New . . . • Faculty advisor: advises several groups. Title Page • Main duty: handle conflicts or emergency situations that required the au- ◭◭ ◮◮ thority of a professor. ◭ ◮ Page 7 of 16 Go Back

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