**3.1.1 Objetives of FESSJ-PROP model**

30 New Research on Knowledge Management Models and Methods

the global society and on behalf of a growing country where the intellectual capital should be distinguished for its formation in architectures and engineering of software, the capacity of investigation, development of intelligent systems, under the paradigms of government of the ICT and of the management information systems, taking care of the environment and in

> **CONTINUITY OF THE CURRICULUM AREAS: BETWEEN 2 CONTIGUOUS CYCLES and**

This Figure 3, emphasizes that propaedeutic cycle education is more robust than the

We have presented a scope of the superior education sector mentioning some critical

One of the most important work we have developed and have been submitted to different

Leontief III Millenium: we present the problem resituation from the Interindustry Economy Model, to the new Knowledge and Information Economy, by recontextualizing the W. LEONTIEF Model from the Industrial Society to the Knowledge Society, and by innovating it with the Process and Knowledge Engineering, Artificial and Computational Intelligence, Fuzzy Logic and General Systems Theory in order to face the most critical problems in Superior Education in Colombia mentioned in the previous Section I. A structural system to

problems we have faced in our research which is presented in the following section.

international scenarios of high technical and scientific, is discussed in this section

**BETWEEN ALL CYCLES**

Fig. 3. Continuity cycle: flexible, sequential and complementary

traditional model: an *all terrain professional*.

**3. Curricular and coherence matrix** 

**3.1 Leontief input output model innovation** 

**2.8 Section I syntehsis** 

defense of the values and life.

The Leontief innovation started by changing the monetary unit by the academic credit as usual in education. The concept of industry at macro-economic level we changed at university micro-economic level and changing by education process: knowledge (of the study plan) and competences as it is illustrated in Figure 4 bellow. It is searches:


#### **3.1.2 Specific objectives**


#### **3.2 Relationships description and architecture**

It refers the logical-cognitive relationships among the architecture parts of an educational system. It is as much an analysis instrument as a linear mathematical structure that communicates (all communication action is a pedagogical one), enabling the justification of a study plan and giving it as an organized and complex totality interlinking the interior and external coherency and consistency. Among the objectives are:


Analytical Models for Tertiary Education by Propaedeutic

subjects involved.

technical coefficients, larger.

during their student life.

and vice versa (2).

academic program.

See Figure 5.

The matrix A is M x N where:

Cycles Applying Knowledge Engineering and Knowledge Management 33

The *COHERENCE* additionally implies: It has the characteristic of holistic and integral view i.e. the entire complexity of the curricular system transcends knowledge in all its conceptual administrative, methodological, educational, normative dimensions. The academy management is coherent with the PEI when the difference between the achieved in face to the wanted is null, curricular coherence. The PEI is the expression of the proper philosophical comprehension of the educational task and it acts as definition of identity,

In this subsection we discuss the Curricular Coherence Matrix which is an arrangement between Competences of the study plan and the knowledge involved in the courses and

The linear model focused on curricular coherence matrix is both an instrument of analysis as a linear mathematical structure, enabling the justification of curriculum and making sense as an organized and complex. The re-contextualization and re-situation Leontief Model Analysis enables Governance and Sustainability with the extension of the matrix A of

The Curricular coherence matrix in a linear arrangement between the knowledge represented in a curriculum and competencies that are expected to develop in students

X = A��Y t= �� (2)

Vector X is the independent or exogenous (1) educational processes related to each subject

The M rows represent levels of competence / expertise of the curricular organization of an

The N columns represent the unit and functional areas (educational processes involving

This cell may contain other qualitative values (fuzzy logic or ambiguity). Each value

�����] = {yes, not} (black, white), or

�����] = {null, medium, high} (white, red, and blue for a dashboard chart).

Next figure we show the whole curricular coherence matrix for Systems Engineering career at the FESSANJOSE with the strategy of the propaedeutical cycles, namely: The Professional Technician in Software Development as the 1st level, the Technology in Software

classes, workshops, tutorials, laboratories, workshops, etc.) knowledge of the Plan.

Y = AX t= �� (1)

exercising the university autonomy, recognized by the Constitution and Law.

**3.3.1 Background: Mathematical Leontief model for systems analysis** 

**3.3 Matrix and sub-matrix applications in curriculum analysis** 

**3.3.2 Generation of a hyperspace matrix for analysis** 

Where Y is the vector of endogenous (1) and vice versa in (2)

represents the incidence between the subject and competition.


The curriculum coherence is the strategic alignment between a study plans with its objectives, justification, given the purpose and view, duly articulated with the PEI:


The external coherence refers to the alignment of the educational style of FESSANJOSE to the professional profiles and intellectual capital which demand the industry, the government, science, and technology in a global society. The model based on educational processes according to the curriculum study plan, where an assignment (including classes, workshops, tutorials, laboratories etc.) is associated to an expertise unit. The matrix method is of morphological type to obtain a system contradictions free without the unwanted entropy. The coherence also implies harmony, and articulation between teaching and apprenticeship, alignment, and synchronization.

The system diagram of the matrix model is expressed as follows: rows representing expertise of each level against columns in which the corresponding curricula subjects is arranged (See the whole Matrix Figure 4).

The link is expressed as a propaedeutic component formed by the intelligent iCOACH in order to increase the student productivity in each cycle and also some assignments of connecting in order to meet the prerequisites of each cycle. It is suggested to have both a terminal cycle with their corresponding competences with and the cycle for following higher levels. We did the design for Systems Engineering and it was presented to obtain the Qualified Register of the program.

Fig. 4. Matrix model system schema



The curriculum coherence is the strategic alignment between a study plans with its


The external coherence refers to the alignment of the educational style of FESSANJOSE to the professional profiles and intellectual capital which demand the industry, the government, science, and technology in a global society. The model based on educational processes according to the curriculum study plan, where an assignment (including classes, workshops, tutorials, laboratories etc.) is associated to an expertise unit. The matrix method is of morphological type to obtain a system contradictions free without the unwanted entropy. The coherence also implies harmony, and articulation between teaching and

The system diagram of the matrix model is expressed as follows: rows representing expertise of each level against columns in which the corresponding curricula subjects is

The link is expressed as a propaedeutic component formed by the intelligent iCOACH in order to increase the student productivity in each cycle and also some assignments of connecting in order to meet the prerequisites of each cycle. It is suggested to have both a terminal cycle with their corresponding competences with and the cycle for following higher levels. We did the design for Systems Engineering and it was presented to obtain the

objectives, justification, given the purpose and view, duly articulated with the PEI: - Non-complex comprehension of the methodology strategy by propaedeutic cycles.

study plan, which gives a sense as an organized and complex totality.




each cycle as well as the know-how.


apprenticeship, alignment, and synchronization.

arranged (See the whole Matrix Figure 4).

Qualified Register of the program.

Fig. 4. Matrix model system schema

analyses.

The *COHERENCE* additionally implies: It has the characteristic of holistic and integral view i.e. the entire complexity of the curricular system transcends knowledge in all its conceptual administrative, methodological, educational, normative dimensions. The academy management is coherent with the PEI when the difference between the achieved in face to the wanted is null, curricular coherence. The PEI is the expression of the proper philosophical comprehension of the educational task and it acts as definition of identity, exercising the university autonomy, recognized by the Constitution and Law.

#### **3.3 Matrix and sub-matrix applications in curriculum analysis**

In this subsection we discuss the Curricular Coherence Matrix which is an arrangement between Competences of the study plan and the knowledge involved in the courses and subjects involved.

#### **3.3.1 Background: Mathematical Leontief model for systems analysis**

The linear model focused on curricular coherence matrix is both an instrument of analysis as a linear mathematical structure, enabling the justification of curriculum and making sense as an organized and complex. The re-contextualization and re-situation Leontief Model Analysis enables Governance and Sustainability with the extension of the matrix A of technical coefficients, larger.

#### **3.3.2 Generation of a hyperspace matrix for analysis**

The Curricular coherence matrix in a linear arrangement between the knowledge represented in a curriculum and competencies that are expected to develop in students during their student life.

$$\mathbf{Y} = \mathbf{A}\mathbf{X} \tag{1}$$

$$\mathbf{t} = \mathbf{A}\mathbf{X} \tag{2}$$

$$\mathbf{X} = \mathbf{A}^{-1}\mathbf{Y} \qquad \qquad \mathbf{t} = T\_1 \tag{2}$$

Where Y is the vector of endogenous (1) and vice versa in (2)

Vector X is the independent or exogenous (1) educational processes related to each subject and vice versa (2).

The matrix A is M x N where:

The M rows represent levels of competence / expertise of the curricular organization of an academic program.

The N columns represent the unit and functional areas (educational processes involving classes, workshops, tutorials, laboratories, workshops, etc.) knowledge of the Plan.

This cell may contain other qualitative values (fuzzy logic or ambiguity). Each value represents the incidence between the subject and competition.

$$\{a\_{i,j}\} = \{\text{yes}, \text{not}\} \text{ (black, white)}, \text{ or } \text{s}$$

�����] = {null, medium, high} (white, red, and blue for a dashboard chart).

See Figure 5.

Next figure we show the whole curricular coherence matrix for Systems Engineering career at the FESSANJOSE with the strategy of the propaedeutical cycles, namely: The Professional Technician in Software Development as the 1st level, the Technology in Software

Analytical Models for Tertiary Education by Propaedeutic

skills or the same knowledge, equation (2)

Technician, as shown in Figure 7.

normalized.

Cycles Applying Knowledge Engineering and Knowledge Management 35

In this work we present the re-contextualized linear model as did Buckley (1992) of the open model of input-output technical coefficients which are expressed by fuzzy numbers. There are some basic assumptions: A process or unit of knowledge can feed one or more competencies. On the other hand provides the linearity between the skills and knowledge. Furthermore the constancy of the technical coefficients of the matrix A is supposed in the medium term. Unlike the Leontief model in which the unit of measure is of monetary type in our unit of measurement is the Academic Credit is properly

Our proposed model makes better use of academic information available. The Leontief model associates industries with academic units in cluster. The corresponding architecture is represented in the Sub-Section 4.5.1, the Table 1. The analysis is based on academic governance system flexibilities of FESSANJOSE as discussed in the sub-section 1.7 and quantified by the equation (1), to observe endogenous or exogenous changes in either the

∆Y =∆AX (3)

*ij j j* ,

Where ݊ is the corresponding subject credits ݀ is the cognitive contribution of the jª subject for each propaedeutic cycle (columns). Bellow contribution in the last row present the cognitive for the first level, Professional Technician on Software Development

*an d*

**3.4.1 Curricular quantification from the matrix: Cognitive contribution**  The cognitive contribution of the jª subject is obtained by the following relation:

corresponding to the Systems engineering matrix depicted in Figure 5.

Fig. 7. Software Development Professional Technician Subjects Contribution

the propaedeutical component correspondent of the previous Technology level.

Similarly for the Technology level of Software Architecture, the cognitive contribution is presented jointly with the propaedeutical component of the 1st level, Professional

For the 3rd Cycle, Professional on Systems Engineering similarly is shown in Figure 9 with

*i*

Architectures as the 2nd cycle and the University cycle in Systems Engineering. All of them rightly articulated by the corresponding Propaedeutical component.

Fig. 5. Systems Engineering Curriculum Coherence Matrix

#### **3.4 Quantitation of curricular knowledge curriculum**

Another chart shows the metric for how well the systmens courses and subjects within each propaedeutic cycle features are integrated to provide specific expertise of the skills deployed in the cross-coherence curricular matrix consistency: from the quantified matrix can be obtain for each cycle the productions in systems, namely in terms of compuational expertise cultivated by the engineering educational process. This type of Matrix can be of several classes, i.e. grouped by areas of knowledge (basics, professional specific, professional, etc), organized in time (by academic semesters of the study plan) and also presented by each propaedeutic cycle with/without articulation. Bellow is presented a way (metaphor) to express a space for the several matrices with fuzzy values just specified earlier.

Fig. 6. Curricular Coherence Matrix hyperspace

Architectures as the 2nd cycle and the University cycle in Systems Engineering. All of them

Another chart shows the metric for how well the systmens courses and subjects within each propaedeutic cycle features are integrated to provide specific expertise of the skills deployed in the cross-coherence curricular matrix consistency: from the quantified matrix can be obtain for each cycle the productions in systems, namely in terms of compuational expertise cultivated by the engineering educational process. This type of Matrix can be of several classes, i.e. grouped by areas of knowledge (basics, professional specific, professional, etc), organized in time (by academic semesters of the study plan) and also presented by each propaedeutic cycle with/without articulation. Bellow is presented a way (metaphor) to

express a space for the several matrices with fuzzy values just specified earlier.

rightly articulated by the corresponding Propaedeutical component.

Fig. 5. Systems Engineering Curriculum Coherence Matrix

**3.4 Quantitation of curricular knowledge curriculum** 

Fig. 6. Curricular Coherence Matrix hyperspace

In this work we present the re-contextualized linear model as did Buckley (1992) of the open model of input-output technical coefficients which are expressed by fuzzy numbers. There are some basic assumptions: A process or unit of knowledge can feed one or more competencies. On the other hand provides the linearity between the skills and knowledge. Furthermore the constancy of the technical coefficients of the matrix A is supposed in the medium term. Unlike the Leontief model in which the unit of measure is of monetary type in our unit of measurement is the Academic Credit is properly normalized.

Our proposed model makes better use of academic information available. The Leontief model associates industries with academic units in cluster. The corresponding architecture is represented in the Sub-Section 4.5.1, the Table 1. The analysis is based on academic governance system flexibilities of FESSANJOSE as discussed in the sub-section 1.7 and quantified by the equation (1), to observe endogenous or exogenous changes in either the skills or the same knowledge, equation (2)

$$
\Delta \mathbf{Y} = \Delta \mathbf{A} \mathbf{X} \tag{3}
$$

#### **3.4.1 Curricular quantification from the matrix: Cognitive contribution**

The cognitive contribution of the jª subject is obtained by the following relation:

$$\sum\_{i} a\_{i,j} n\_j = d\_j \tag{4}$$

Where ݊ is the corresponding subject credits ݀ is the cognitive contribution of the jª subject for each propaedeutic cycle (columns). Bellow contribution in the last row present the cognitive for the first level, Professional Technician on Software Development corresponding to the Systems engineering matrix depicted in Figure 5.


Fig. 7. Software Development Professional Technician Subjects Contribution

Similarly for the Technology level of Software Architecture, the cognitive contribution is presented jointly with the propaedeutical component of the 1st level, Professional Technician, as shown in Figure 7.

For the 3rd Cycle, Professional on Systems Engineering similarly is shown in Figure 9 with the propaedeutical component correspondent of the previous Technology level.

Analytical Models for Tertiary Education by Propaedeutic

the same for the University cycle.

**OPERATIONAL COMMUNICATION** 

**DEVELOPMENT** 

**EVOLUTION**

Engineering.

**MAINTENACE AND** 

**TECHNICAL SOFTWARE** 

**PROBLEMS DEFINITION**

**PROBLEM SOLVING**

**ENTREPRENEURSHIP**

**TRAINING ON RESEARCH** 

**TECHNICAL-PROFESSIONAL COMPETENCES**

by the competences of the 1st cycle of Technician-Professional.

**TECHNICAL-PROFESSIONAL Level**

**Propedeutical of TP**

Cycles Applying Knowledge Engineering and Knowledge Management 37

The Figure 10 bellow shows the values of Expertise cultivated in the student for each cycle,

The Figure 11 expresses the same by the competences of the Technology cycle. The Figure 13

**ACADEMIC CREDITS 77 15 92 <sup>45</sup>** 9 ## **26 172**

Fig. 10. Expertise cultivated in the student for each cycle, by the competences of the 1st cycle

In the diagram of the Figure 5 it can be seen how they develop skills throughout student academic life. It is noted that development of basic skills is permanent or continuous Salthouse (1991) backed by numerous studies in which skill or expertise has a behavior of someone who continually learns, throughout his life: a Normal Distribution. This may be associated with the occupational skills of the three cycles preliminary in Systems

**3.5.1 Systems engineering skills by cycles, expertise and know-how**

**TOTAL TP Cycle**

**52 27 79 87 6 93 12 105**

**Propedeutical of Technology**

**TOTAL Ciclo Tecnológico**

**University Component**

**Total of University Component**

**Technology Level**

**60 24 84 95 12 107 16 123**

**18 6 24 45 6 51 12 63**

**36 12 48 43 0 43 6 49**

**64 15 79 77 3 80 18 98**

**36 9 45 77 3 80 4 84**

**36 6 42 54 9 63 0 63**


Fig. 8. SoftwareArchitecture Technology Subjects Contribution: TP articulated


Fig. 9. 3rd cycle Professional on Systems Engineering Subjects Contribution technology articulated

These values (added by subjects) for each subject to compare the cognitive contribution per semester and also allows:

To identify orphan subjects which have not been established or are too weak implications. To identify any overestimation

The above would require a review by the Curriculum Expert Group.

#### **3.5 Other metrics obtained from the matrix: Production**

The cultivated expertise is given by the production i as follows:

$$\sum\_{j} a\_{i,j} n\_j = b\_i \tag{5}$$

Where ܾ is the ݅ production, expressed as cultivated expertise for each competence unit (rows). For each cycle see bellow the corresponding values obtained.

Fig. 8. SoftwareArchitecture Technology Subjects Contribution: TP articulated

Fig. 9. 3rd cycle Professional on Systems Engineering Subjects Contribution

The above would require a review by the Curriculum Expert Group.

(rows). For each cycle see bellow the corresponding values obtained.

**3.5 Other metrics obtained from the matrix: Production**  The cultivated expertise is given by the production i as follows:

These values (added by subjects) for each subject to compare the cognitive contribution per

*i*, *j j i*

Where ܾ is the ݅ production, expressed as cultivated expertise for each competence unit

*an b* (5)

*j*

To identify orphan subjects which have not been established or are too weak implications.

technology articulated

semester and also allows:

To identify any overestimation

The Figure 10 bellow shows the values of Expertise cultivated in the student for each cycle, by the competences of the 1st cycle of Technician-Professional.

The Figure 11 expresses the same by the competences of the Technology cycle. The Figure 13 the same for the University cycle.


Fig. 10. Expertise cultivated in the student for each cycle, by the competences of the 1st cycle

#### **3.5.1 Systems engineering skills by cycles, expertise and know-how**

In the diagram of the Figure 5 it can be seen how they develop skills throughout student academic life. It is noted that development of basic skills is permanent or continuous Salthouse (1991) backed by numerous studies in which skill or expertise has a behavior of someone who continually learns, throughout his life: a Normal Distribution. This may be associated with the occupational skills of the three cycles preliminary in Systems Engineering.

Analytical Models for Tertiary Education by Propaedeutic

ORGANIZATIONAL KNOWLEDGE

CREATIVITY FOR THE IDENTIFICATION OF PROBLEMS AND THEIR SOLUTION

ENTERPRISE ARCHITECTURE

SOLUTION ENGINEERING PROBLEMS

USABILITY SYSTEMS ENGINEERING

ENTERPRICE AND ICT GOVERNANCE

MANAGERIAL SYSTEMS

ENTERPRICE INTELLIGENCE

integration, design and composition (synthesis).

**PROFESSIONAL CYCLE COMPETENCES**

cycle

Cycles Applying Knowledge Engineering and Knowledge Management 39

**Propedeutical of TP**

**TECHNICAL-PROFESSIONAL Level**

**ACADEMIC CREDITS 77 15 92 45** 9 146 **26 172**

**TOTAL TP Cycle**

**0**

Fig. 12. Expertise cultivated in the student for each cycle, by the competences of the 3rd


entrusted him/her to social responsibility and civic commitment.

from the machine communication, working with people is required.




**43 10 53 74 6 80 36 116**

**Technology Level**

**Propedeutical of Technology**

**TOTAL Ciclo Tecnológico**

**University Component**

**Total of University Component**

**44 9 53 66 9 75 40 115**

**147 15 162 169 9 178 40 218**

**24 9 33 46 9 55 40 95**

**38 10 48 58 6 64 44 108**

**21 7 28 21 6 27 24 51**

**52 5 57 52 9 61 24 85**

**2 2 0 6 6 16 22**

The Systems Professional expertise requires the definition of specialized skills or outstanding tasks i. e. SUPERIOR PERFORMANCE or represented in a domain that are described as KNOW HOW. The cognitive processes associated with learning mechanisms are of more complex.

EXPERTISE approach involves the development of skills as a dynamic continuum and is associated with learning processes throughout life that are affected by change and social practices, industry behavior, science and technology. As a result, the structure of competence is variable in itself, change usually associated with a requirement of living space in which it is used. In concluding synthesis:


Fig. 11. Competences cultivated in the student for each cycle, by the competences of the 2nd cycle

Analytical Models for Tertiary Education by Propaedeutic Cycles Applying Knowledge Engineering and Knowledge Management 39

38 New Research on Knowledge Management Models and Methods

The Systems Professional expertise requires the definition of specialized skills or outstanding tasks i. e. SUPERIOR PERFORMANCE or represented in a domain that are described as KNOW HOW. The cognitive processes associated with learning mechanisms

EXPERTISE approach involves the development of skills as a dynamic continuum and is associated with learning processes throughout life that are affected by change and social practices, industry behavior, science and technology. As a result, the structure of competence is variable in itself, change usually associated with a requirement of living space

Fig. 11. Competences cultivated in the student for each cycle, by the competences of

are of more complex.

the 2nd cycle

in which it is used. In concluding synthesis:


Fig. 12. Expertise cultivated in the student for each cycle, by the competences of the 3rd cycle


Analytical Models for Tertiary Education by Propaedeutic

Can you explain the lower/higher values?

Fig. 13. Feedback and Feedforward Matrices

**higher education** 

proposed, after changes?

demand?

terms?

Cycles Applying Knowledge Engineering and Knowledge Management 41

What if a new competence is included due to the Systems, Software and related industries

What is the effect of restructuring a subject or a course or a subset of them in missionary

Is it necessary to recalculate the number of credits assigned to each subject initially

**4. Education software architecture: Facing student desertion in Colombia** 

The Student Desertion National wide problem is very critical by its cultural, economics and family impact. Several IES (Superior Education Institutions) have performed studies leading to point out this problem as a recurrent and prevalent one. The design and implementation of iCOACH which is an intelligent tool knowledge based is presented here as a instrument of high computing to follow up each student in the academic first terms of the engineering faculty at the FESSANJOSE, The software architecture have 3 main parts: Edumatic builder

Is it necessary to revise a subject content regarding the competence impact? Is it necessary to redefine the scope and the limitation of a competence? Is it a group of subjects of the study plan, biased or underestimated?


The imperative demands of ICT and its domain expertise in different environments as enshrined in the Colombia National Plan of ICT, but the recent ICT Law passed by the local Government.

#### **3.5.2 Inputs skills / expertise in systems engineering**

For each of the cycles shows the quantification of the lecturing services, extension, research, mentoring, support, laboratories, experiment, practice and other which is acquired by every competence in the cognitive process of each student.

In these plots, the row number refers to the number of credits each course feeding the competence offered in this cycle: Professional Technician on Software Development.

Each value allows us to visualize the relative importance of a subject. If zero or very low one, tells us that is isolated or de-contextualized and deserves a critical review.

The model of the first cycle of the FESSANJOSE provides five semesters, has been successful in the national context, obtaining several years in the top ECAES (professional examinations of official national wide). The technology cycle visualize the design possibilities and advantages of this cycle. Applying the formulas (1) and (2) we obtain the corresponding values for competences cultivated for each propaedeutic cycle and the valued added of the courses. See Figures 10, 11 and 12.

#### **3.6 Input / otput matrix**

In this matrix each cell is expressed as follows:

$$
\widetilde{\mathbf{u}}\_{l,f} = \frac{d\_l}{b\_l} \tag{6}
$$

Technical Coeficient: input fraction by production unit: Where each ǡ coefficient is the ratio of cognitive inputs by unit of cultivated competence production.

With this matrix (called of the technical coefficients), it can be performed the OPTIMIZATION analysis, adding quality objectives, capacity restrictions as costs, academic objectives, scholars population, lecturers, university resources and many others related. Also this matrix can be extended to complete the Leontief I/O matrix with the remaining sectors as shown in the Table 1 of the sub-section 4.1.4.

The Systems Engineering curriculum design based in propedeutical cycles and also in EXPERTISE have cognitive and structural features distinctive, the first of which is an academic structure articulated, sequential, complementary and flexible, whose cornerstone is the development of professional and occupational engineering skills. This assumption allows defining: Firstly the **Feedback sub-matrix** corresponding to the cycle objective, which can be quantified knowledge articulation, processes subsequent courses to strengthen the competencies implied. See Figure 13 bellow.

The **Feedforward sub-matrix,** to quantify the knowledge articulation of the processes of the current cycle and feeding skills training for senior cycle (upper).

There are many possibilities for analysis, to meet the socio-economics demands in terms of such competences.

Are they balanced?

Is there bias?

What if a new competence is included due to the Systems, Software and related industries demand?

What is the effect of restructuring a subject or a course or a subset of them in missionary terms?

Can you explain the lower/higher values?

40 New Research on Knowledge Management Models and Methods


The imperative demands of ICT and its domain expertise in different environments as enshrined in the Colombia National Plan of ICT, but the recent ICT Law passed by the local

For each of the cycles shows the quantification of the lecturing services, extension, research, mentoring, support, laboratories, experiment, practice and other which is acquired by every

In these plots, the row number refers to the number of credits each course feeding the

Each value allows us to visualize the relative importance of a subject. If zero or very low

The model of the first cycle of the FESSANJOSE provides five semesters, has been successful in the national context, obtaining several years in the top ECAES (professional examinations of official national wide). The technology cycle visualize the design possibilities and advantages of this cycle. Applying the formulas (1) and (2) we obtain the corresponding values for competences cultivated for each propaedeutic cycle and the valued added of the

(6)

ൌ Ǥ

ratio of cognitive inputs by unit of cultivated competence production.

Technical Coeficient: input fraction by production unit: Where each ǡ coefficient is the

With this matrix (called of the technical coefficients), it can be performed the OPTIMIZATION analysis, adding quality objectives, capacity restrictions as costs, academic objectives, scholars population, lecturers, university resources and many others related. Also this matrix can be extended to complete the Leontief I/O matrix with the remaining

The Systems Engineering curriculum design based in propedeutical cycles and also in EXPERTISE have cognitive and structural features distinctive, the first of which is an academic structure articulated, sequential, complementary and flexible, whose cornerstone is the development of professional and occupational engineering skills. This assumption allows defining: Firstly the **Feedback sub-matrix** corresponding to the cycle objective, which can be quantified knowledge articulation, processes subsequent courses to strengthen the

The **Feedforward sub-matrix,** to quantify the knowledge articulation of the processes of the

There are many possibilities for analysis, to meet the socio-economics demands in terms of

competence offered in this cycle: Professional Technician on Software Development.

one, tells us that is isolated or de-contextualized and deserves a critical review.

the global Millennium III: this is the imperative of our research.

**3.5.2 Inputs skills / expertise in systems engineering** 

competence in the cognitive process of each student.

courses. See Figures 10, 11 and 12.

In this matrix each cell is expressed as follows:

sectors as shown in the Table 1 of the sub-section 4.1.4.

current cycle and feeding skills training for senior cycle (upper).

competencies implied. See Figure 13 bellow.

such competences. Are they balanced? Is there bias?

**3.6 Input / otput matrix** 

Government.

Is it necessary to revise a subject content regarding the competence impact?

Is it necessary to redefine the scope and the limitation of a competence?

Is it a group of subjects of the study plan, biased or underestimated?

Is it necessary to recalculate the number of credits assigned to each subject initially proposed, after changes?

Fig. 13. Feedback and Feedforward Matrices
