Құрастырушы: Құрастырушылар: аға оқытушы Успанова А. И

6. COURSE CONTENT

1. 
   Gerard Morgan and Seamus O’Neill. Essential Computer Applications. Third edition. Gill and Macmillian. 2000. 303 p.
   
2. 
   Makarova N.V., Volkov V.B. Informatica. SPb: Piter, 2011. 576 p.
   
3. 
   Dzhumagaliyeva A.M., Nurgazinova A.Zh., Smailova L.K., Kulmuratova A.Sh. Informatics. Almaty: ZhShS RPBK «Dauir», 2011. – 248 p.
   
4. 
   Simonovich S.V. Informatics. Base course (textbook for higher education). 2 issue. SPb: Piter, 2004. 640 p.
   
5. 
   Akulov O.A., Medvedev N.V. Informatics. Base course. M.: Omega-L, 2005. 552 p.
   
6. 
   Stepanov A.N. Informatics: Textbook for higher education. 4 issue. SPb: Piter, 2006. 684 p.
   
7. 
   Sovetov B.Y., Cehanovskii V.V. Information technology. М.: Higher school, 2006. 263 с.
   
8. 
   Stepanov A.N. Architecture of information system and computer network. SPb: Piter, 2007.
   

9. 
   Jenny Preece. Human – Computer interaction. Addison – Wesley publishing company, Wokinham, England, 1994.
   
10. 
    Encyclopedia of Computer Science.  2003 John Wiley & Sons, Ltd.
    
11. 
    Carl Hamacher V., Zvonko G.Vranesic, Safwat G.Zaky, «Computer organization», Tata McGraw Hill, Latest Edition.
    
12. 
    Heuring V.P., Jordan H.F., «Computer System Design and Architecture», Addison Wesley, 2009.
    
13. 
    Patterson and Hennessey, «Computer organization and Design». The Hardware/Software interface, Harcourt Asia Morgan Kaufmann, 2009.
    
14. 
    Hayes, «Computer Architecture and Organization», Tata McGraw Hill, 2008.
    
15. 
    Trivedi K.S. «Probability and Statistics with reliability, Queuing and Computer Science Applications», Prentice – Hall of India, New Delhi, 2004.
    
16. 
    Balagurusamy E., «Reliability Engineering», Tata McGraw Hill Publishers, New Delhi, 2004.
    
17. 
    Gross D. and Harris C.M., «Fundamentals of Queuing Theory», John Wiley &Sons, 2008.
    
18. 
    Allen, A.O., «Probability Statistics and Queuing Theory», Academic Press, 2001.
    

The running control on a laboratory training, Office Hours, SDW.

Intermediate control: Computer test

Final control: Examination

• Not to be late for classes, to be punctual and obligatory.

• Not to miss the classes (in the absence in the case of illness to provide the reference).

• Missed classes to fulfill during the time defined by the teacher.

• Not to talk during the classes, not to read the newspaper, to disconnect the cell phone.

• Participate actively in the educational process.

• To be tolerant, open, frank and benevolent to classmates and teachers.
11. Policy of mark estimates
Scheme of the discipline knowledge assessment

	Types of trainings and works of students	Points quantity min/max
I	Running control Lectures Labortary lessons OH (tasks performance)	15 week* 1 p = 15 p/7,5 p 15 week* 1 p = 15 p/7,5 p 15 week* 0,66 p = 10 p/5 p
II	Intermediate control:	2 week * 10 = 20 p/ 10 p
	Total:	30/60 points
III	Final control: Examination	20/40 points
	Total:	60/100 points

Scale of students’ knowledge assessment

Mark on alphabetic system	Points of digital equivalent	Percentage of points	Mark on the traditional system
А	4,0	95-100	excellently
А-	3,67	90-94
В+	3,33	85-89	good
В	3,0	80-84
В-	2,67	75-79
С+	2,33	70-74	satisfactorily
С	2,0	65-69
С-	1,67	60-64
D+	1,33	55-59
D	1,0	50-54
F	0	0-49	unsatisfactorily

PART 1. LECTURES

Lecture 1. An introduction to information
Before deciding to explorer the four application areas outlined in this book, we must have some basic background knowledge of computing. To use a comparison: before beginning to drive a car on the road we need to have some idea of th working of gears and other equipment in the car. We also need to know the rules of the road. Similary, before using computers we should know about the equipment and procedures we are likely to use.

In this lecture we will cover the following areas:

• 
  An introduction to information.
  
• 
  Hardware.
  
• 
  Data communications.
  
• 
  Software.
  
• 
  Data processing.
  
• 
  The information technology environment.
  

Figure 1 - Data processing to produce information

• 
  What examples do you know about data and information?
  
• 
  Name variuos type of information process?
  

There are seven generic information-processing tasks: Scanning, Selecting, Capturing, Storing, Creating, Communicating, and Implementing. In general, this set of tasks is performed in sequential fashion beginning with scanning and ending with implementation. In reality, however, these tasks may be performed out of sequence. In some cases a person or group may even skip a step. The information-processing framework presented below is an attempt to categorize and describe the entire spectrum of information-processing tasks performed by individuals, groups, and organizations. These tasks are presented in a sequence that tends to occur naturally in organizations and other social situations (Figure 2).

Figure 2 – Seven generic information-processing tasks

One day, Arman decides it's time buy a new car. This is a big investment for John, and, as you would suspect, he wants to make the best possible decision. John begins searching (scanning) for information that will help him make the right decision. He begins searching the Internet, talking to friends and car dealers, and purchases an automobile buyers guide at the local bookstore. With so many information sources and car models available, John decides he must narrow his search and chooses to focus on mid-sized sport utility vehicles (SUVs) and the Internet and a buyer’s guide he recently purchased for fact-finding purposes (selecting). John documents his research findings in an spreadsheet (capturing) where he lists the performance characteristics and attributes of various mid-sized SUVs. This spreadsheet is maintained on the hard drive of his home computer (storing). John is pressured by his wife to make a decision the following week. The next day, Armani examines the spreadsheet information, interprets it, and produces an overall score for each SUV he is considering buying (creating). Arman communicates his findings to his wife (communicating) and together they make a final decision. The next day they buy their new car (implementing), and Arman and his wife live happily ever after. Arman has performed all seven of the generic information-processing tasks to reach his final decision.

Once a source (or sources) of information is selected for processing purposes, the next step is to capture information. Obtaining information is the act of gathering it at its point of origin. This information-processing task is performed by input computer technologies such as the keyboard or a bar code reader. From an individual perspective, your eyes and ears capture information.

Information-processing systems often require a mechanism for storing information so it can be used and/or reused later on. Storage devices include the human brain, notes, libraries, hard drives in a computer, and computer databases. Organizations store information in policy manuals and in their cultural practices, traditions, and habits.

Once information has been captured, it must now be interpreted and/or processed. Creating this interpretation involves the cognitive process of drawing a conclusion as to the meaning of information. This can be a very subjective process performed by decision makers. Meaning attached to information is often the result of the categories or labels that people use. Information can be interpreted as positive or negative, reliable or unreliable, relevant or irrelevant, as a threat or an opportunity. These are just a few of the possibilities. How one interprets information influences the actions one will take in response. This is key to understanding how our perceptions influence our behavior, and how the same information might lead to different types of actions, depending on who is interpreting it. This task also involves processing information to obtain new information. Many computer software packages exist to analyze data and produce new forms of information for the user.

The actions one may take usually involve change. Change can range from small-scale forms, such as changes in procedures, to larger-scale forms, such as revisions in overall corporate strategy. How one translates information into action often determines the end results or performance outcomes. Performance outcomes may include feelings of satisfaction, increased profits, increased market share, change in behavior, customer satisfaction, and many others.

Figure 3 – Data, Information, Knowledge

1. 
   The company's computer is capable of processing 10,000 customer requests an hour.
   
2. 
   The company receives an average of 9800 customer requests an hour.
   
3. 
   The company's stock price was $62 per share. Each fact, by itself, is relatively meaningless because we have little or no context within which to evaluate and make sense of it.