In this study, we took college students studying in higher vocational colleges as the research subjects, and considering the difficulty of the experiment, we only selected five higher vocational colleges in Hefei, Anhui Province, namely Anhui Vocational and Technical College, Anhui University of Finance and Economics, Anhui Changjiang Vocational College, Anhui Professional College of Art, and Anhui Vocational and Technical College of Forestry. The five selected colleges had high reputation and teaching quality in the local area.

The questionnaires were distributed in two ways: offline and online. The offline research was mainly conducted by going to five colleges during the weekend, 150 questionnaires were filled out; the online research was mainly conducted by using Questionnaire Star to generate web links and invite students at random and ask them to forward them to their friends’ circle, 300 questionnaires were distributed. A total of 450 questionnaires were distributed among the research process, and 306 valid questionnaires were obtained after eliminating invalid questionnaires, with a valid rate of 68%.

There were 202 female respondents, accounting for 66.0%. Other details about characteristics of the respondents, including age, annual family income and majors, were all shown in Table 1.

The questionnaire involved in this study included 17 variables: information acquisition behavior, self-directed learning ability, innovative learning ability,

continuous learning ability, teamwork ability, systematic thinking ability, low self-efficacy, anxiety, lack of curiosity, weak problem awareness, insufficient innovation motivation, poor self-monitoring ability, poor self-regulation ability, insufficient team awareness, team slacking behavior, poor information criticism ability, and poor information thinking ability. These variables were measured using a Likerts-5 point scale. In the questionnaire, “1” stands for “Very Inconsistent”, “2” stands for “Inconsistent”, “3” stands for “Not Sure”, “4” stands for “Consistent”, and “5” stands for “Very Consistent”.

The CITC values of all items in the questionnaire were greater than the minimum standard value of 0.3 and the Cronbach’s Alpha coefficient values were greater than the minimum acceptable value of 0.7, which indicates a high level of consistency and stability among the items, an excellent level of reliability. In addition, the values of “alpha coefficients of deleted items” were not significantly different from the values of alpha coefficients, indicating that all items should be retained and that the reliability level of the study data is high and can be used for further analysis.

The validity test was to test the degree of validity of the questionnaire, and the indicator adopted by most of the current literature was construct validity, which was mainly divided into convergent validity and differential validity. The SFL (Standardized Factor Loading) values, AVE (Average Variance Extracted) values and CR (composite reliability) values of 17 variables of this study were greater than 0.5, indicating that the sample had good convergent validity.

In this study, gender, age, household income, and profession were selected as control variables for this paper, and the first step was to conduct a general demographic variable analysis of the study population. In this paper, we only considered the differences in the five indicators of information acquisition ability, namely, independent learning ability, innovative learning ability, continuous learning ability, teamwork ability, and systematic thinking ability, and did not further develop the group differences in low self-efficacy, anxiety, lack of curiosity, and so on. On the one hand, a large amount of data about these factors was difficult to analyze; on the other hand, other factors all impact college students’ information acquisition ability by influencing the above five variables. So it was enough to analyze the above 5 variables for this research.

The differences between the five variables in terms of gender were analyzed. Means, Standard Deviations, F-values, T-values and P-values for different genders were listed in Table 2. No significant differences emerged between genders in self-directed learning ability, innovative learning ability, continuous learning ability, teamwork ability, and systematic thinking ability.

Since there were too many majors involved in the questionnaire survey, here we just divided them into two major categories: natural science and social science. The differences of the five variables between the 2 majors were analyzed. Means, Standard Deviations, F-values, T-values and P-values for different majors were listed in Table 3. According to the results, we could find that there were no significant difference on continuous learning ability and teamwork ability between the 2 majors, while independent learning ability, innovative learning ability and systematic thinking ability show significant differences. Students’ perceptions of innovative learning ability in natural science were greater than those students of social science, and students’ perceptions of independent learning ability and

systematic learning ability in social science were greater than students of natural science.

Table 4 shows the relationship between these 17 variables, where latent variables, non-standardized values, standard deviation and standardized values were listed. First, the five dimensions of ability including independent learning ability, innovative learning ability, continuous learning ability, teamwork ability, and systematic thinking ability are all important influences on information acquisition. Similarly, the p-value significance also indicates that self-directed learning ability can be explained by three dimensions: low desire for knowledge, low self-efficacy and excessive anxiety, the barriers to innovative ability are insufficient problem awareness and insufficient motivation to innovate, the main barriers to continuous learning behavior are their poor self-monitoring ability and self-regulation. The

main influencing factors of teamwork ability are weak team awareness and team slacking, and the main influencing factors of systematic thinking ability are poor information criticism and information thinking ability.

The hardware foundation of the school is crucial to the information ability of college students. Based on the development of the times, the school uses micro-media technology VR technology and other technologies as a more ideal form of teaching, giving full play to the good immersion and interactivity of these technologies to effectively increase students’ interest in learning computers and make students build up their own interest in learning. By combining traditional cultural knowledge instillation with advanced technology, and combining new media technology to evaluate and match each student’s ability and needs, we can enrich the way of education for students, expand the way of inputting information sources for students, and change the traditional passive teaching of “filling the classroom” to new media teaching that gives full play to students’ initiative.

First of all, a large and sufficient number of professional lectures are beneficial to greatly broaden students’ interest in various knowledge, and only by enhancing their interest will students have sufficient motivation to learn and explore on their own. Secondly, more industrial projects can be carried out with enterprises and social organizations, which not only help students to improve their understanding of practice and society, but also help them to develop their problem-solving ability, but the school needs to make more efforts to strictly control the relevant projects to avoid being formal, etc. Third, schools can cooperate more with other schools to promote more communication between student teams.

High school is a crucial step for students to enter the society, and it is also a key step for students to say goodbye to their youth and realize their growth. Students at this stage are usually confused about their future. Therefore, schools must be concerned with the direction of students’ lives rather than their academic performance, which is the original purpose of school education. On the other hand, they can also regularly invite students who have graduated earlier to speak for the current students and help them understand their future better by giving speeches about their own understanding of society and work. Secondly, for higher vocational institutions, they can contact more units and enterprises to enrich students’ learning experience and practical experience, so as to increase their understanding of work and career, only in this way will students know what kind of person they will be, what kind of occupation they will engage in and what kind of career development they will have in the future, which will help students determine their career goals, and then determine the current learning goals and This will help students determine their career goals, and then determine their current learning goals and knowledge learning content, which is the inner motivation to effectively increase students’ initiative to search for information, explore knowledge and learn knowledge.

Higher schools’ evaluation system has an important impact on teachers’ teaching and students’ growth. Score-only undoubtedly constrains creativity, but in practice schools are still centered on the score system because it is the simplest method to operate, while quality-based evaluation means more resources would be invested. On the one hand, the solution to this dilemma requires the initiative of teachers to improve their creative teaching performance; on the other hand, higher schools need take the lead in promoting professional dialogue and knowledge co-construction between teachers and external professionals can be used as an alternative.