“…To Achieve Excellence by Guiding Individuals as They Develop the Proficiency, Expertise, and Leadership Consistent with Their Professional Roles”

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College of Education and Health Professions                                                   Columbus State University

Department of Teacher Education

 

Course Information Sheet

Course:

EDUT 5455G – Practicum in Computer Science (2 credit hours)

Conceptual_Framework

Semester:

Summer 2011

Instructor:

  Wayne Summers / Jacob Crowder

Time:

Online

Office:

 CCT 453

Day(s):

Online

Phone:

(706) 568-2410

Location:

Online

Email:

wsummers@columbusstate.edu /

crowder_jacob@columbusstate.edu

 

 

FAX:

 

Teaching Schedule:

June 13-17

July 18-22

Office Hours:

M-F 10-noon or via email

Prerequisites:

 

 

 

 

 

 

Corequisites:

CPSC2105 and CPSC 2108 with grades of C or better and CPSC 5135U or CPSC 5157U

 

EDUT 5125U  - Methods in Computer Science

 

 

 

The College of Education and Health Professions at Columbus State University prepares highly qualified teachers, counselors, and leaders who promote high levels of learning for all P-12 students by demonstrating excellence in teaching, scholarship, and professionalism. Teachers, counselors, and leaders continually acquire, integrate, refine, and model these qualities as they develop proficiency, expertise, and leadership. COE faculty guide individuals in this developmental process. 

 

Teaching, scholarship, and professionalism encompass the highest standards represented in the five (5) core assumptions of accomplished teaching of the National Board of Professional Teaching Standards (NBPTS). The Department of Teacher Education has adopted these principles and assumptions, which are listed below, as standards for advanced teachers.

 

NBPTS Core Assumptions:

1.      Teachers are committed to students and their learning.

2.      Teachers know the subjects they teach and how to teach   those subjects to students.

3.      Teachers are responsible for managing and monitoring student learning.

4.      Teachers think systematically about their practice and learn from experience.

5.      Teachers are members of learning communities.

 

ADA Compliance Statement

If you have a documented disability as described by the Rehabilitation Act of 1973 (P.L. 933-112 Section 504) and Americans with Disabilities Act (ADA) and would like to request academic and/or physical accommodations please contact Joy Norman at the Office of Disability Services in the Center for Academic Support and Student Retention, Tucker Hall (706) 568-2330, as soon as possible. Course requirements will not be waived but reasonable accommodations may be provided as appropriate.

 

Course Description:

Opportunity to apply what is learned in other courses to real classroom situations. The candidate will have experiences in observing, planning, instructing, and evaluating in a computer science classroom.

 

Course Goals and Objectives

Knowledge:

Upon successful completion of this course, candidates will:

1.      demonstrate knowledge of various methods of effective teaching specific to Computer Science

2.      demonstrate knowledge of the learning process of 6-12 grade students and how individuals differ in their approaches to learning, including differences associated with English Language Learners

3.      demonstrate knowledge of planning processes based upon knowledge of content, learner characteristics, the community, and curriculum goals and standards

4.      demonstrate knowledge of a variety of strategies and methods that enhances the development of critical thinking and problem solving skills

5.      demonstrate knowledge of effective verbal, nonverbal, and media communication techniques that can foster active inquiry, collaboration, and supporting interactions between a student and a teacher

6.      demonstrate knowledge of methods of evaluating a learner’s development and understanding of the subject

7.      demonstrate knowledge of educational research and how to apply that knowledge when planning and teaching lessons

 

Skills:

Upon successful completion of this course students will:

1.      demonstrate the ability to effectively teach Computer Science to 6-12 grade students, including English Language Learners

2.      demonstrate the ability to provide students with opportunities that support intellectual, career, social, and personal development

3.      demonstrate the ability to use various instructional software and tools in a classroom setting.

4.      demonstrate the ability to effectively evaluate performance of each student

5.      demonstrate the ability to effectively evaluate own performance as a teacher

6.      demonstrate ability to apply educational research when planning and teaching lessons

                                                           

Course Requirements

Students are expected to:

·         Spend a minimum of 60 hours during the semester in a computer science classroom setting (e.g., local school, evening classes, summer camps), including at least 15 hours of observation at a local school (grades 6-12) that includes basic Computer Science in its curriculum; 

·         Teach a unit in a grades 6-12 computer science classroom, in evening classes specially arranged with high school student participants, or in summer camps for high school students organized by the TSYS School of Computer Science. Candidate will plan and teach a unit under the guidance of a cooperating teacher and/or university supervisor

·         Maintain a weekly log of professional activities

·         Write a weekly reflection on observations and other practicum experiences

·         Conduct a teaching evaluation survey to be completed by each student in classes taught by the endorsement candidate

·         Write a reflection paper on implementation of teaching unit, making connections to the research on best practices in teaching Computer Science and the various techniques for supporting different learning styles including those techniques needed to support English Language Learners.

 

Grades:

Teacher candidates will be observed in the classroom setting by the university supervisor and/or via video. Teacher candidates will be evaluated on aspects of teaching described in the Model of Accomplished Practice (MAP). The MAP outlines the skills advanced teachers should demonstrate in the five domains of (1) commitment to students and their learning, (2) knowledge of subjects taught and how to teach those subjects to students, (3) managing and monitoring student learning, (4) thinking systematically about practice and learning from experience, and (5) participation in learning communities. Cooperating teachers (if applicable) will also be asked to complete a MAP evaluation and a Dispositions evaluation at the end of the semester. The university supervisor will collect the forms. Rubrics for the Model of Accomplished Practice (MAP) and the Dispositions evaluation can be found at the following web site: http://te.ColumbusState.edu/forms.asp .

 

Evaluation:

Weekly log – 10%

Weekly reflections – 20%

Teaching unit – 20%

Reflection paper – 20%

Performance assessments (MAP & Dispositions) – 30%

 

Grading Scale:

90-100             A

80-89               B

70-79              C

60-69               D

Below 60         F

Textbook: None

Cultural Diversity: In keeping with the Columbus State University Creed, membership in our community of scholars obligates us to practice personal and academic integrity; respect the dignity of all persons; respect the rights and property of others; celebrate diversity, strive to learn from differences in people, ideas, and opinions; demonstrate concern for others, their feelings, and their need for support in their work and development.  Perspectives on the importance of cultural diversity on the various topics will be included in the discussions.

 

Technology: Students will be using the broad range of electronic technology available in the University's computer laboratories and library. Resources available include, but are not limited to, Copernic, Peachnet, Galileo, and SilverPlatter; search engines include Hotbot, Inference Find, Metacrawler, Dogpile, MetaFind, Yahoo!, Infoseek, Alta Vista, Lycos, and Northern Light.

 

Attendance Policy: Regular attendance at class or a laboratory is a student obligation.  Hours of absence in excess of nine (9) in this three-semester hour course will cause you to be dropped from the class for excessive absence (CSU 2003-2004 Catalog, p. 67) (on internet that equals to three non participation times).

 

Plagiarism:

The appropriation of passages, either word for word or in substance, from the writing of another and the incorporation of those passages as one’s own in written work offered for credit. It is always assumed that the written work offered for credit is the student’s own unless proper credit is given the original author by the use of quotation marks and footnotes or other explanatory inserts. This includes the copying of laboratory reports and homework, or the unchanged use of the essential ideas or conclusions of such work, as well as the footnoted use of other themes, theses, books, or pamphlets.  NOTE:  Plagiarism may come about through carelessness or ignorance.  Every student, however, may free him/herself from uncertainties on this score by observing the special practice by each instructor for preparation of written work in his/her particular course.

 

COURSE OUTLINE (tentative)

DATE

Assignments

Activities

Assessments

Week 1:

(June 13-17)

 

Teach Lego Robots camp

Observe Dr. Ray

MAP & Dispositions

Week 2:

(June 20-24)

Week 1 log

Week 1 reflection

Observe Dr. Yang

Observe Jason Cornwell

 

Week 3:

(June 27-July 1)

Week 2 log

Week 2 reflection

Observe Dr. Ray

Observe Dr. Obando

 

Week 4:

(July 5-8)

Week 3 log

Week 3 reflection

 

 

Week 5:

(July 11-15)

Week 4 log

Week 4 reflection

Observe Dr. Ray

Observe Dr. Obando

 

Week 6:

(July 18-22)

Week 5 log

Week 5 reflection

Teach Lego Robots camp

Observe Dr. Yang

MAP & Dispositions

Week 7:

(July 25-28)

Week 6 log

Week 6 reflection

Observe Dr. Yang

Reflection paper due

 

Week 8:

(July 31)

Week 7 log

Week 7 reflection