CN106408475A - Online course applicability evaluation method - Google Patents
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Abstract
The invention discloses an online course applicability evaluation method which belongs to the technical field of intelligent recommendation. Based on the analysis of the personal learning characteristics of a learner and online course teaching policies, the method establishes a correlation model for the personal characteristics and the learning effect of the learner by statistically calculating the personal learning characteristics and the online course learning effect of a large numbers of learners. The correlation model is used to predict the learning effect of the learner in a course to be selected. According to prediction results, the learner is helped to select the most suitable course for learning, namely a course with the best prediction result is selected for learning. According to the method, the learner can easily find the course suitable for the personal characteristics from a large number of course resources, so that the learning effect is improved; and in addition, the method can help the learner to better understand the details of the selected course in the aspect of teaching style and the like, so that the weaknesses of the learner can be effectively overcome in learning.
Description
Technical field
The invention belongs to intelligent recommendation technical field is and in particular to a kind of online course fitness-for-service assessment method.
Background technology
With the development of information technology, more and more personalized learning systems for self-study and course are opened
Send out.On-line study has gradually been given play to important in the school eduaction of different phase and the teaching process of all kinds of adult education
Effect.It is related to the on-line study resource of every subjects, even same section purpose online course resource occurs in network in large quantities
Above although substantial amounts of education resource provides more choices for learner, but this also makes how learner is selecting to be suitable for
Occur in that new puzzlement in the online course aspect of oneself.
In order to lift the results of learning of online course, researcher all over the world has carried out substantial amounts of research.Wherein main
The aspect wanted is the quality how lifting teaching resource, for example, add the table that a large amount of multimedia elements can be more lively in courseware
The existing content of courses is thus reducing learning difficulty and lifting the interest of learner.Another study hotspot is to increase the interaction between teaching
With guiding, for example many scholars to evaluate various influence factors and results of learning using different evaluation methods, and then to teaching
Resource is targetedly improved.In addition, the application of artificial intelligence data digging technology can also help educator to obtain
More targeted teaching data, thus provide new new way for lifting results of learning.
Although lifted online results of learning have been obtained for more and more paying attention to, CAL person from numerous
The method of suitable course is selected but to be rarely reported in line course.With the development of on-line study, increasing educational institution and
Educator is devoted to developing online course so that a large amount of same subject but has the class of various teaching style and instructional strategies
Journey opens to learner.Obviously, it is not that every a branch of instruction in school is adapted to each learner.According to the research of forefathers, as study
Learner's features such as style, learning motivation, learning behavior mode and rudimentary knowledge can significantly affect on-line study effect.In other words
Say, if the styles of teaching of course and instructional strategies are consistent with the personal touch of learner, on-line study effect can obtain
Lifting.So, designing a kind of fitness-for-service assessment method that learner can be helped to carry out suitable course selection is that one kind is lifted at
The effective way of line results of learning.
OCAA (On-line course applicability assessment, online course fitness-for-service assessment) is base
On-line study effect prediction method in learner's feature statistical analysis.According to the research of forefathers, learning style, learning behavior side
Formula and rudimentary knowledge are that the important of impact on-line study effect can quantitative factor.
1st, the impact to on-line study effect for the learning style
Learning style refers to the personalized mode of learning of learner, including carrying out creative thinking, information processing, knowledge
The tendentiousness feature having when memory and Resolving probiems.Substantial amounts of research shows learning style and course teaching as learner
When strategy is consistent, results of learning will get a promotion.The content of courses according to designed by learner's learning style can improve study
Efficiency simultaneously makes learner have more preferable performance.The proper classification of learning style can be made a distinction simultaneously to learner effectively
Targetedly help for its offer.
As described previously for the different learner of learning style, by select suitable learn content can be lifted its
The effect of line study.So, the present invention is evaluated to the learning style of learner using learning style evaluation method, thus obtaining
Know whether selected course is consistent with its learning style.The research of forefathers shows, Felder- in online learning environment
Accuracy in terms of distinguishing different-style learner for the early stage model of Silverman is up to 71%.In addition, learning phase with tradition
On-line study has its unique property to ratio.Such as learning and exchange process is substantially complete by way of vision and the sense of hearing
Become, and the autonomous learning of learner occupies leading position in whole learning process.Therefore, " vision ＆ auditory type learner "
Classification more meet on-line study feature, and the study of " concluding ＆ reasoning " type also has significantly during autonomous learning
Different.Analyzed based on above, learning Style Evaluation of the present invention is by the Felder being delivered according to 1988 Silverman style
Model is designed.
2nd, the impact to on-line study effect for the learning behavior mode
The less-restrictive to learner for the on-line study, learner can be learned with place according to demand at any time
Practise.But, unconfined academic environment needs learner to have clear and definite learning motivation and require higher self-disciplining.Self-disciplining
The management of study requirement learner's active and the learning behavior adjusting complexity.Heikkila and Lonka thinks from type of law learner
Clear and definite learning objective can be set and work out detailed study plan, the initiative learning can be kept and study can be executed well
Plan.Research shows that self-disciplining has important effect for the on-line study effect of lifting learner.According to Hu and
The research of Gramling, self-disciplining is very important to the enthusiasm during lifting learner's on-line study.On the contrary, dragging
Postpone a meeting or conference and lead to the reduction of on-line study effect and various problems concerning study may be caused.According to the research of Pintrich, from the type of law
Practise three kinds of learning strategy types main inclusion below：
1) cognitive learning strategy：This type can apply to simply remember inquiry learning (for example to word, form etc.
Memory) or more complicated it is understood that knowledge.
2. from type of law strategy：Be used for managing from type of law strategy, the cognitive activities of Schistosomiasis control person itself and practice behavior.
3. policy in resource management：The environment that this strategy is applied to learner's management and controls it to be located.
In the present invention, adopt and evaluated to assess the self-discipline of learner based on the learning behavior mode of Pintrich evaluation model
Sexual behaviour and learning motivation.According to this evaluation result, the high learner of self-disciplining can select to constrain less online course,
And these learners can be autonomous formulation study plan.And for the poor learner of self-disciplining, then need selection to have more
The online courses instructing with detailed teaching programme more.
3rd, the impact to on-line study effect for the rudimentary knowledge
Rudimentary knowledge is one of main factor of impact results of learning.The rudimentary knowledge of association area can affect to learn
The learning effect of person.It is generally acknowledged that preferable rudimentary knowledge level can help lift results of learning, simultaneously mistake or not
Perfect rudimentary knowledge can affect results of learning.The research of Mitchell etc. finds the learner with varying level rudimentary knowledge
Different cognitions can be produced to on-line study content, thus affecting their results of learning.Rudimentary knowledge poor learner exist
Studying new knowledge will face more challenges when knowing, and they need more to assist and guide.Thompson and Zamboanga thinks
Student and teacher can benefit from rudimentary knowledge is evaluated, and it can make teacher obtain more useful information so as to root
Situation according to student targetedly adjusts instructional strategies.So carried out before study starts rudimentary knowledge evaluation contribute to pre-
Survey the learning performance of student.Meanwhile, rudimentary knowledge evaluation can provide advantage before learned lesson for the student and deficiency etc. related
Detailed information, so that teacher knows in which link to need especially to be paid close attention to.
The key of rudimentary knowledge evaluation is to determine that the rudimentary knowledge of which type needs to be evaluated.Dochy is by base
Plinth knowledge is divided into declarative and procedural knowledge two types.Declarative knowledge is construed to " knowing that what is " by Anderson,
And procedural knowledge is construed to " why know ".Research finds that different evaluation methods are suitable for different types of basis and know
Know.It is therefore possible to use different evaluation methods is evaluated to different types of rudimentary knowledge.The present invention is by learner's
Declarative and Process Character rudimentary knowledge is evaluated respectively.
Content of the invention
For the puzzlement overcoming learner to occur in terms of how selecting to be suitable for the online course of oneself, help learner
Select to be suitable for the online course of oneself feature, the present invention provides a kind of online course Adaptability Evaluation (OCAA) method, described side
Method can analyze the relevance between online course instructional strategies and learner's learning characteristic, and then predicts learner to this course
Results of learning, thus helping learner to choose the suitable online course of oneself.
For realizing above-mentioned target, the present invention employs the following technical solutions：
A kind of online course Adaptability Evaluation Method, methods described is in statistical analysis learner's self-study feature, online
On the basis of course teaching strategy, carried out by the self-study feature to a large amount of learners and the results of learning to online course
Statistical computation, sets up the correlation model between learner personal touch and results of learning, then adopts described correlation model to
Results of learning in course to be selected for the habit person are predicted, and the result according to prediction helps learner to pick out optimal course
Learnt, that is, select the optimal course that predicts the outcome and learnt, thus lifting results of learning.
Described learner's self-study feature includes learning style, learning behavior mode and rudimentary knowledge.
Described online course instructional strategies includes the content of courses, class hour, teaching programme, learning cycle, guidance, discussion
With exchange way, exercise and operating type, Assessment.
Using learning style evaluation method, the learning style of learner is evaluated, thus knowing whether selected class
Journey is consistent with its learning style.
Preferably, according to the Felder Silverman Style Model design learning Style Evaluation method delivered for 1988.
Adopt evaluated based on the learning behavior mode of Pintrich evaluation model with the self-discipline sexual behaviour of assessing learner and
Learning motivation.According to this evaluation result, the high learner of self-disciplining can select to constrain less online course, and these
Learner can be autonomous formulation study plan.And for the poor learner of self-disciplining, then need selection have more instruct and
The online course of detailed teaching programme.
The basis based on the Educational Psychology dimension sorting technique of the knowledge classification method of Bloom and Dochy is adopted to know
Know evaluation method, the declarative of learner and Process Character rudimentary knowledge are evaluated respectively.
A kind of online course fitness-for-service assessment method, comprises the following steps：
1) test the characteristics of personality of learner；
2) analyze the instructional strategies of online course；
3) associative learning person feature, the course teaching strategy and learner results of learning to course, carry out statistical analysis and
Calculate, set up online course fitness-for-service assessment model, i.e. OCAA model；
4) utilize OCAA model, prediction has the learner of specific characteristics of personality to the online class with various teaching strategy
The results of learning of journey；
5) guidance learning person selects the optimal online course of prediction effect as learning object.
Advantages of the present invention and having the beneficial effect that：The reason of online course fitness-for-service assessment method (OCAA) of the present invention
By basis it is：In online learning environment, the learning style of student, learning behavior mode and rudimentary knowledge all can be produced to results of learning
Raw impact.When the personal touch of learner is consistent with the styles of teaching of selected course and instructional strategies, it will have preferably
Results of learning.By the statistical analysis to collected data, OCAA can predict the results of learning in corresponding course for the learner,
In prediction, the higher course of score will be more suitable for this learner.Therefore, OCAA can make learner from substantial amounts of course resources
In easier find the course being suitable for personal touch so as to results of learning get a promotion.In addition, OCAA can help learn
Person is best understood from the details at aspects such as styles of teachings for the selected course, thus can be weak efficiently against itself in study
Point.
Specific embodiment
A kind of online course Adaptability Evaluation Method, in statistical analysis learner's self-study feature, online course teaching
On the basis of strategy, carry out statistics meter by the self-study feature to a large amount of learners and the results of learning to online course
Calculate, set up the correlation model between learner personal touch and results of learning, then using described correlation model, learner is existed
Results of learning in course to be selected are predicted, and the result according to prediction helps learner to pick out optimal course
Practise, that is, select the optimal course that predicts the outcome and learnt, thus lifting results of learning.
Described learner's self-study feature includes learning style, learning behavior mode and rudimentary knowledge.
Described online course instructional strategies includes the content of courses, class hour, teaching programme, learning cycle, guidance, discussion
With exchange way, exercise and operating type, Assessment.
Using learning style evaluation method, the learning style of learner is evaluated, thus knowing whether selected class
Journey is consistent with its learning style.
Preferably, according to the Felder Silverman Style Model design learning Style Evaluation method delivered for 1988.
Adopt evaluated based on the learning behavior mode of Pintrich evaluation model with the self-discipline sexual behaviour of assessing learner and
Learning motivation.According to this evaluation result, the high learner of self-disciplining can select to constrain less online course, and these
Learner can be autonomous formulation study plan.And for the poor learner of self-disciplining, then need selection have more instruct and
The online course of detailed teaching programme.
The basis based on the Educational Psychology dimension sorting technique of the knowledge classification method of Bloom and Dochy is adopted to know
Know evaluation method, the declarative of learner and Process Character rudimentary knowledge are evaluated respectively.
Described online course fitness-for-service assessment method, comprises the following steps：
1) test the characteristics of personality of learner；
2) analyze the instructional strategies of online course；
3) associative learning person feature, the course teaching strategy and learner results of learning to course, carry out statistical analysis and
Calculate, set up online course fitness-for-service assessment model, i.e. OCAA model；
4) utilize OCAA model, prediction has the learner of specific characteristics of personality to the online class with various teaching strategy
The results of learning of journey；
5) guidance learning person selects the optimal online course of prediction effect as learning object.
Embodiment
The present embodiment selects three different " JAVA language " courses of instructional strategies to be compared experiment, thus setting up OCAA
Evaluation model simultaneously verifies its validity and using effect.
1st, participant and course
The feature of table 1 experimental courses and styles of teaching
The personnel participating in this experiment include sophomore (the inclusion schoolgirl of 3 teachers and 186 computer majors
47 people, boy student 139 people).The teacher participating in has the Web-based instruction and guidance experience, and student is familiar with online course learning.Experiment quilt
It is divided into two stages, correspondingly student is randomly divided into two groups, be first stage group (S-1, n=91) and second-order respectively
Section group (S-2, n=95).
Before starting course learning, the personal touch of each student is evaluated respectively.In S-1 group, student
Course can be freely selected to be learnt.The relation between student personal touch and results of learning will be studied in this stage.
In next stage, the student of S-2 group carries out course selection under the guidance of OCAA and completes the study of course.
Three difficulty of selection quite but tested by different online " Java language programming " course of instructional strategies.In order to build
Vertical OCAA model, needs to carry out evaluation analysis to the feature of every subject.Data according to early stage and analysis expert, in reality
Before testing beginning, the styles of teaching of every subject and teaching environment are all carried out evaluating and summary (referring to table 1).Three teachers
Instructor respectively as every subject gives student necessary guidance in learning process.
2nd, essential elements of evaluation
2.1 online course fitness-for-service assessment
This research is directed generally to disclose learner personal touch affecting and setting up OCAA model to on-line study effect
Selected with helping learner to be more effectively carried out online course from substantial amounts of course resources.The study of impact on-line study effect
Person's feature mainly includes learning style, learning behavior mode and rudimentary knowledge.These features can be by carrying out one before giving a course
The survey analysis of series and knowledge test obtain.Each above-mentioned feature can be to study effect during on-line study
Fruit produces positive or negative effect.Relation between learner personal touch and learning performance can be used for evaluating and predicts
Line results of learning.Therefore, this experiment is wished to set up online course fitness-for-service assessment (OCAA) by test data and statistical analysis
Model.The foundation of OCAA model is to aid in learner and selects suitable online course to enter from substantial amounts of Network Learning Resource
Row study.In this experiment, the foundation of OCAA model includes two key links：(1) according to S-1 group obtain students ' characteristics with
Analyze data sets up results of learning forecast model；(2) OCAA model-aided S-2 group is applied to carry out course choosing according to personal touch
Select.By OCAA model it is desirable to make the student of different characteristics can obtain the auxiliary of personalization during on-line study and draw
Lead thus lifting its results of learning.In addition, this experiment is compared thus to OCAA's to the results of learning of S-1 group and S-2 group
Validity is verified.In order to complete two groups of comparison, three subjects will be carried out after class using the paper of Similar content and difficulty
Test.
2.2 learning style evaluations
The learning style assessment item of this experiment is according to the Felder Silverman learning style model delivered for 1988
Design.Evaluate and so that it is simplified as far as possible to complete this, this experiment inscribes a 25 topics of questionnaire designs according to the 44 of Felder
Questionnaire.By the research and analysis one by one to Felder-Soloman questionnaire, and therefrom have selected be suitable for online course and this
The respective entries of experiment.Meanwhile, the purpose of the feature according to on-line study and this experiment, our also asking of part of designed, designed
Topic.By these entries being combined completing the design of learning style questionnaire.In this questionnaire, each classification is right respectively
Should there are 5 problems.In questionnaire, each classification is all evaluated (as shown in table 2) according to 5 grades.The result of 5 grades is respectively
Tendency degree in the evaluation of this learning style for the reflection learner.For example：" active " is tended in ' Active+ ' expression very much
Style, ' Active ' represents and compares and tend to " active " style, but its intensity to be weaker than ' Active+ ' and than ' Neutral '
It is eager to excel.In addition, ' Neutral ' represents do not have obvious tendentiousness in a certain genre classification.
The classification of table 2 learning style questionnaire result and grade
In order to show the matching degree of learner's learning style and course features, according to above-mentioned students' learning style evaluation
Course style in result and table 1 has carried out corresponding calculating.Matching degree in this experiment includes overall learning style
Join the learning style matching degree (md of degree (S) and each classificationLS-1,mdLS-2,mdLS-3,mdLS-4and mdLS-5).mdLS-x's
Value is arranged between 1～5.For a course being suitable for " active " style, the learner of ' Active+ ' can obtain
5 points of (mdLS-1=5), ' Active ' learner can obtain 4 points and ' Reflective+ ' learner can obtain 1 point of (mdLS-1
=1), by that analogy.Other courses and learner feature (mdLS-2,mdLS-3,mdLS-4and mdLS-5) adopt identical method
Calculated.The value (100points) of S is calculated by below equation：S=4 × (mdLS-1+mdLS-2+mdLS-3+mdLS-4+
mdLS-5), it reflects the matching degree with course teaching style for the learning style of learner.Therefore, the value of S not only with learner
Learning style relevant, and relevant with the styles of teaching of selected course.
2.3 learning behavior modes are evaluated
Learning behavior mode evaluates self-discipline ability and learning motivation for investigating learner.The research of this part with
Based on the self-disciplining theories of learning of Pintrich.Learning behavior mode is evaluated and will be examined whether the learning behavior mode of learner
Can be effectively facilitated them participate in on-line study and promote their selfdiscipline to lift results of learning.This experimental design
The questionnaire (100 points, often inscribe 5 points) that portion comprises 20 problems is investigated to the learning behavior mode of student.The exercise question of questionnaire
Relate generally to the contents such as the target of behavior student learns in the past in and this study.Each problem comprises 3 or 5 choosings
Item is (for example for problem：Whether you are interested in this subject？Option is：Very interested, interested, general, less feel emerging
Interest, lose interest in).For the problem comprising 5 options, each option corresponds to 1～5 point of score value, and for three options
Problem, the score value of corresponding 1 point of each option, 3 points or 5 points.Final point can be obtained by being added to the score of each problem
Number (is represented with alphabetical " B ").For similar course, the value of B is only relevant with the feature of learner, will not be with class
Cheng Butong and occur change.But for different courses, need different learning behavior modes and its instructional strategies phase
Coupling, therefore learning behavior mode is evaluated and will be played a role in course selection.
2.4 rudimentary knowledge evaluations
Rudimentary knowledge evaluation in this experiment is used for testing learner to study " Java language programming " course necessity knowledge
Grasp situation.Experiment adopts based on the Educational Psychology dimension sorting technique of the knowledge classification method of Bloom and Dochy
Rudimentary knowledge evaluation method, both sorting techniques are widely adopted in educational research.Grinding according to Hailikari et al.
Study carefully, rudimentary knowledge evaluation is divided into two parts, including declarative knowledge evaluation and procedural knowledge evaluation.Both bases are known
Know and be subdivided into two types (as shown in table 3) respectively again.
Part and its feature that table 3 rudimentary knowledge is evaluated
Based on above rudimentary knowledge evaluation theory, this experimental design comprises 25 declarative knowledge problems (with " dk "
Represent, totally 50 points, often inscribe 2 points) and 10 procedural knowledge problems (being represented with " pk ", 50 points, often 5 points of topic) questionnaire.Statement
Sex knowledge test is primarily directed to the related notion of Java language programming, and procedural knowledge test is primarily upon programming aspect
Practical problem.The result (being represented with alphabetical " K ") that rudimentary knowledge is evaluated then is added acquisition by dk with the value of pk.With learning behavior side
The result of formula is similar to, and the value of K is also only relevant with the personal touch of learner.But different courses is wanted for rudimentary knowledge
Ask different, so rudimentary knowledge evaluation will be helpful to the selection of online course, when particularly consideration together with other factorses.
Therefore, the rudimentary knowledge evaluation achievement of student will carry out statistical together with the evaluation result of learning style and learning behavior mode
Analysis.
3rd, experimental design
In the present embodiment, OCAA model will be set up by experimental technique.It is personal special to student first when experiment starts
Point is evaluated.Next, experiment will be divided into two stages：In the first stage, the student of S-1 group can be freely from course
Select course in A, course B and course C and complete this study under the guidance of teacher.Learner personal touch and results of learning it
Between relation will be analyzed using statistical method.Carry out correlation based on the experiment of first stage and statistic analysis result
Calculate thus setting up the OCAA model of 3 experimental courses.In next stage, S-2 different from the form of S-1 group Free-Select-Course
The student of group carries out curricula-variable according to the evaluation result of OCAA.The course that two groups of students are learnt is identical, and completes in course
Tested afterwards to understand the study situation of student.
This experiment takes following program to carry out：Introduce the mentality of designing of this experiment, class to the teacher participating in experiment first
The contents such as journey details, teaching method, then all of student's participation learning style, learning behavior mode and rudimentary knowledge evaluation.
Subsequently, S-1 group student unrestricted choice course within the time of 2 months, course learning is carried out by computer.After study terminates
S-1 group student is tested to understand its study situation.Then pass through statistical method to S-1 group students ' characteristics and results of learning
The data of aspect is analyzed and sets up OCAA model.In the second stage of experiment, OCAA auxiliary S-2 group student carries out curricula-variable,
And identical with S-1 group complete course in 2 months.Finally, by being compared to the final result of S-1 group and S-2 group student
Thus testing the using effect of OCAA.
4th, Data Collection and analysis
The research data collected is needed to include：(1) learning style evaluation, learning behavior mode are evaluated and rudimentary knowledge evaluation
Fraction；(2) fraction tested after class.All of data will be analyzed using IBM SPSS Statistics software.
This experiment adopts the computational methods of following 4 types.First, using Pearson came relative analysis method S-1 group
Linear dependence between raw final test achievement (T) and three feature evaluation results.Substantially have with final testing result
The parameter of linear dependence is using the independent variable as next step regression analysis.Second, T is set up using multi-element linear regression method
Discussion of Linear Model and various independents variable between.The OCAA model of course A, course B and course C will be according to multiple linear regression
The result of analysis is set up.3rd, it is (final that the feature evaluation result according to S-2 group student carries out results of learning using OCAA model
Test result) prediction.Student will select the OCAA best course that predicts the outcome to be learnt.Finally, by variance analysis side
Method compares the school grade of two groups of students, thus understanding effect in terms of lifting online results of learning for the OCAA.
5th, result and discussion
5.1 correlation analysis results
First, using final test achievement (T) and three kinds of feature evaluations of student of Pearson came relative analysis method S-1 group
Linear dependence between result (B, S, K), it the results are shown in Table 4.
Table 4 S-1 group T and B, the correlation analysis between S, K
**p<0.01.
The result of calculation of table 4 shows, in course A, learning style (p<0.01) and learning behavior mode (p<0.01) all
There is obvious positive correlation with final total marks of the examination, and rudimentary knowledge (p>0.05) there is no obvious positive with final total marks of the examination
Close, so when carrying out regression analysis to course A, parameter K should be excluded from independent variable.The reason cause this phenomenon possible
It is to comprise enough rudimentary knowledge contents in course A to help student to understand course content, even so rudimentary knowledge is poor
Student also will not the final result be caused significantly affect.For course B, learning style (p<0.01) and rudimentary knowledge
(p<0.01) all there is obvious positive correlation with final total marks of the examination, and learning behavior mode (p>0.05) with final total marks of the examination
There is no obvious positive correlation.Therefore will not significantly affect final total marks of the examination in course B learning behavior, to course
When B carries out regression analysis, parameter B should be excluded from independent variable.This is because course B comprises detailed teaching programme, student
Only need to be learnt without voluntarily making a plan by existing teaching programme.According to the analysis result of course C in table 4, learn
Style (p<0.01), learning behavior mode (p<0.01) and rudimentary knowledge (p<0.01) all exist significantly with final total marks of the examination
Positive correlation, shows that these three factors all can significantly affect the final total marks of the examination of course C.
5.2 regression analyses and results of learning forecast model
In this experiment, using multiple linear regression analysis method between final test achievement (T) and each independent variable
Linear relationship be modeled.Determine the independent variable of selected three subjects according to the result of correlation analysis, then adopt IBM
SPSS Statistics software carries out multiple linear regression and sets up multiple linear regression equations with all argument datas to T.
SPSS analysis result is shown in Table 5, table 6 and table 7.
List the summarized results of all variables in table 5.Determine coefficient (R2) show in course A, course B and course C
Total explanation amount of variability difference 84.1%, 96.3% and 94.9% produced by independent variable.
Table 5 S-1 group model collects
aPredictive variable：(constant), BCourse A, SCourse A
bPredictive variable：(constant), SCourse B, KCourse B
cPredictive variable：(constant), BCourse C, SCourse C, KCourse C
Subsequently, using variance analysis, above-mentioned model is tested.According to the assay of table 6, course A, course B and class
The value of the F test statistics of journey C is respectively 71.496,367.601 and 161.214, and corresponding probability P value is respectively 0.002,
0.000,0.001, respectively less than 0.01.Under 0.01 significance, independent variable has aobvious to multivariate regression models for this explanation
The impact writing.
Table 6 S-1 group Anovad
aPredictive variable：(constant), BCourse A, SCourse A
bPredictive variable：(constant), SCourse B, KCourse B
cPredictive variable：(constant), BCourse C, SCourse C, KCourse C
dDependent variable：T
T assay (table 7) according to independent variable parameter, the significance of three subjects is respectively less than 0.05, shows class
Independent variable in journey A, course B and course C all has significant impact to T value.
Table 7 S-1 group coefficienta
aDependent variable：T
According to above-mentioned analysis and inspection, the linear of three subjects can be set up according to variation coefficient listed in table 7
Regression model equation.The equation of linear regression of three subjects being obtained according to nonstandardized technique coefficient is as follows：
TCourse A=11.037+0.507B+0.407S
TCourse B=9.327+0.385S+0.474K
TCourse C=7.644+0.205B+0.405S+0.299K
This model shows that the coefficient of each variable and final total marks of the examination (T) are positive correlation.In addition, for different
Course, learner's feature for the influence degree of on-line study effect and differs, the styles of teaching of its influence degree and course
There is very big relation with strategy.
The application of 5.3OCAA and on-line study effect
According to experimental arrangement, S-2 group student selects under the auxiliary of OCAA from course A, course B and course C tri- subject
Select suitable course.Learning style based on S-2 group student, learning behavior mode and rudimentary knowledge evaluation result and linear return
Return equation, each student of this group has been carried out with the results of learning prediction of three experimental courses.According to predicting the outcome, this group student
Select to predict the outcome best course being learnt on request.The curricula-variable result of S-1 group and S-2 group student and final examination
Average achievement is shown in Table 8.
The curricula-variable result of table 8 S-1 group and S-2 group student and average achievement of finally taking an examination
In order to check the using effect of OCAA, using variance analysis, S-1 group is become with the finally examination of the every subject of S-2 group
Achievement compares.Before carrying out variance analysis, the homogeneity of variance of three subject data is checked, its result is all higher than
0.05, show that the variance of three subjects meets homogeneity of variance and requires.The result of variance analysis is as shown in table 9.
Table 9 S-1 group and the one-way analysis of variance of the final total marks of the examination of S-2 group
aAdjustment Multiple range test：Bonferroni.
Selected three subjects for this experiment, table 9 lists the final total marks of the examination tool between S-1 group and S-2 group
There is significant difference (p<0.05).In other words, in this experiment, the use of OCAA has significantly for the results of learning of student
Impact.In addition, according to Bonferroni average result of the comparison, in three subjects of this experiment, the auxiliary Students ' in OCAA is equal
There is preferable performance.
6. experiment conclusion
In this experiment, the instructional strategies analysis of our personal touch based on learner and specific online course establishes
OCAA method.S-1 group test result indicate that, the learning style of student, learning behavior mode and rudimentary knowledge are to on-line study
Effect all has significant impact.In addition, for different courses, the impact journey to results of learning for the above-mentioned three kinds of personal touch
Spend and differ.This has its unique instructional strategies mainly due to every subject, its to student different aspect individual
Feature has different requirements.In S-2 group, by the guidance of OCAA, student can carry out curricula-variable according to its personal touch.From S-
The variance ratio of the final total marks of the examination of 1 and S-2 group student relatively understands, can obtain bright in the results of learning of the auxiliary Students ' of OCAA
Aobvious lifting.
The theoretical foundation of OCAA is：In online learning environment, the learning style of student, learning behavior mode and rudimentary knowledge
All impact can be produced on results of learning.When the personal touch of learner is consistent with the styles of teaching of selected course and instructional strategies
When, it will there are preferable results of learning.By the statistical analysis to collected data, OCAA can predict learner in corresponding class
The results of learning of journey, in prediction, the higher course of score will be more suitable for this learner.Therefore, OCAA can make learner from
Easier in substantial amounts of course resources find the course being suitable for personal touch so as to results of learning get a promotion.In addition,
OCAA can help learner to be best understood from the details at aspects such as styles of teachings for the selected course, thus can have in study
Effect ground overcomes the weakness of itself.
Finally it should be noted that：Obviously, above-described embodiment is only intended to clearly illustrate example of the present invention, and simultaneously
The non-restriction to embodiment.For those of ordinary skill in the field, can also do on the basis of the above description
Go out change or the variation of other multi-forms.There is no need to be exhaustive to all of embodiment.And thus drawn
The obvious change stretched out or change among still in protection scope of the present invention.
Claims (8)
1. a kind of online course Adaptability Evaluation Method it is characterised in that：Methods described is in statistical analysis learner's self-study
On the basis of feature, online course instructional strategies, by the self-study feature to a large amount of learners and to online course
Practise effect and carry out statistical computation, set up the correlation model between learner personal touch and results of learning, then adopt described pass
To learner, the results of learning in course to be selected are predicted gang mould type, and the result according to prediction helps learner to pick out more
Suitable course is learnt, that is, select the optimal course that predicts the outcome and learnt, thus lifting results of learning.
2. as claimed in claim 1 a kind of online course Adaptability Evaluation Method it is characterised in that：Described learner's personalogy
Habit feature includes learning style, learning behavior mode and rudimentary knowledge.
3. as claimed in claim 1 a kind of online course Adaptability Evaluation Method it is characterised in that：Described online course teaching
Strategy includes the content of courses, class hour, teaching programme, learning cycle, guidance, discusses and exchange way, exercise and operator
Formula, Assessment.
4. as claimed in claim 1 or 2 a kind of online course Adaptability Evaluation Method it is characterised in that：Using learning style
Evaluation method is evaluated to the learning style of learner, thus knowing whether selected course and its learning style phase one
Cause.
5. a kind of online course Adaptability Evaluation Method as described in claim 1,2 or 4 it is characterised in that：Preferably, according to
The Felder-Silverman Style Model design learning Style Evaluation method that 1988 deliver.
6. as claimed in claim 1 or 2 a kind of online course Adaptability Evaluation Method it is characterised in that：Using being based on
The learning behavior mode of Pintrich evaluation model evaluates self-discipline sexual behaviour and learning motivation to assess learner.
7. as claimed in claim 1 or 2 a kind of online course Adaptability Evaluation Method it is characterised in that：Adopt with Bloom's
Rudimentary knowledge evaluation method based on the Educational Psychology dimension sorting technique of knowledge classification method and Dochy, to learner's
Declarative and Process Character rudimentary knowledge is evaluated respectively.
8. as claimed in claim 1 a kind of online course fitness-for-service assessment method it is characterised in that methods described include following
Step：
1) test the characteristics of personality of learner；
2) analyze the instructional strategies of online course；
3) associative learning person feature, the course teaching strategy and learner results of learning to course, carry out statistical analysis and calculating,
Set up online course fitness-for-service assessment model, i.e. OCAA model；
4) utilize OCAA model, prediction has the learner of specific characteristics of personality to the online course with various teaching strategy
Results of learning；
5) guidance learning person selects the optimal online course of prediction effect as learning object.
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