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Advances in Social Sciences Research Journal – Vol. 11, No. 9

Publication Date: September 25, 2024

DOI:10.14738/assrj.119.17641.

Shengnan, C., Jiansheng, H., Lei, D., Shuanghui, S., & Chao, W. (2024). Exploring Effective Paths for Artificial Intelligence to

Empower Freshmen's Autonomous English Learning in an “Internet Plus” Environment. Advances in Social Sciences Research

Journal, 11(9). 261-280.

Services for Science and Education – United Kingdom

Exploring Effective Paths for Artificial Intelligence to Empower

Freshmen's Autonomous English Learning in an “Internet Plus”

Environment

Chen Shengnan

Zhiyuan School of Liberal Arts, Beijing Institute of Petrolchemical Technology,

Beijing, No.19, Qingyuan North Road, Daxing District, Beijing, P.R. China

Hu Jiansheng

Zhiyuan School of Liberal Arts, Beijing Institute of Petrolchemical Technology,

Beijing, No.19, Qingyuan North Road, Daxing District, Beijing, P.R. China

Ding Lei

Zhiyuan School of Liberal Arts, Beijing Institute of Petrolchemical Technology,

Beijing, No.19, Qingyuan North Road, Daxing District, Beijing, P.R. China

Sun Shuanghui

Zhiyuan School of Liberal Arts, Beijing Institute of Petrolchemical Technology,

Beijing, No.19, Qingyuan North Road, Daxing District, Beijing, P.R. China

Wang Chao

Zhiyuan School of Liberal Arts, Beijing Institute of Petrolchemical Technology,

Beijing, No.19, Qingyuan North Road, Daxing District, Beijing, P.R. China

ABSTRACT

In the environment of "Internet plus", the combination of artificial intelligence

technology and education has broken the time and space limitations of autonomous

learning, subversively changed the way students learn, and brought more

possibilities and challenges to both teachers' "teaching" and students' "learning". It

brings more possibilities and challenges for both teachers' "teaching" and students'

"learning". This study takes the freshmen non-English majors of Beijing Institute of

Petrochemical Technology as the research object, based on the multiple

intelligences theory and the constructivist learning theory, investigates the status

and ability of freshmen's autonomous learning of English in the context of the era of

"Internet plus", and explores the effects of the learning tools and learning

environments supported by the new technology of artificial intelligence on

students’ autonomous learning ability and learning effect. It explores the impact of

learning tools and learning environment supported by the new technology of

artificial intelligence on students’ autonomous learning ability and learning effect,

so as to further explore the effective path to improve students' English autonomous

learning ability. It provides empirical data support and suggestions for autonomous

learning research and university English teaching, and facilitates teachers to make

scientific adjustments in the selection of teaching content, monitoring of teaching

platforms, design of teaching activities, and application of teaching methods to

promote the improvement of students' autonomous learning ability, and at the

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Advances in Social Sciences Research Journal (ASSRJ) Vol. 11, Issue 9, September-2024

Services for Science and Education – United Kingdom

same time, it also helps students to identify their problems in autonomous learning,

find effective paths to solve the problems, and improve their learning efficiency.

Keywords: Internet plus, freshmen, English autonomous learning, learning paths

INTRODUCTION

The arrival of the artificial intelligence era has not only changed the way we live, but also the

way we learn, especially in today's accelerating rate of knowledge updating, the ability to learn

autonomously has become a basic quality that college students are expected to have. In the

environment of "Internet plus", the in-depth integration of artificial intelligence and learning

analytics technology has made personalized learning possible, and students can choose

adaptive learning content according to their own learning preferences and differences. In- depth investigation of students’ autonomous learning in the "Internet plus" environment, and

explore its effective path, the use of empirical data to help teachers make scientific adjustments

in the selection of teaching content, monitoring of teaching platforms, design of teaching

activities, and the use of teaching methods, in order to promote the improvement of students'

ability to learn independently, and at the same time help students to At the same time, it also

helps students to recognize their problems in autonomous learning, find effective paths to solve

them, and improve their learning efficiency.

CHANGES IN LEARNING IN THE INTERNET PLUS ENVIRONMENT

The traditional mode of teaching requires that lessons be conducted at a fixed time and place,

which is not possible if students or teachers are absent, thus affecting the conduct and

effectiveness of teaching. Lack of teaching resources, if only based on textbooks, teaching guides

and teachers' experience, then the content of learning is also limited, students can not get more

learning materials.

The Internet does not have this disadvantage, teachers and students can break through the

limitations of time and space, information and knowledge exchange and learning, and further

enhance the learning effect. Students have more autonomy, in terms of resource selection, to

learn a new language skill, he can choose the micro-teacher's micro-teaching in the school, but

also in the catechism platform to choose a famous teacher's lectures. Learning time is more

casual, learning place is not restricted, learning progress is more flexible, as long as there are

smart devices and wireless network students can learn independently anytime, anywhere, and

at the same time can be repeated many times, breaking the traditional classroom time, space

and the disadvantages of the limited mode of instruction.

Self-directed learning, active learning, cooperative learning and personalized learning are the

main ways of learning for university English students in the era of "Internet +". The wide

application of the Internet enhances the openness of knowledge, classroom and teachers are no

longer the only way for students to acquire knowledge, and students can obtain diversified

learning resources more conveniently and quickly through the Internet. The classroom is no

longer just a place for knowledge transfer, but a place for teachers to guide students to master

learning strategies and answer questions. The combination of classroom teaching and modern

technology broadens the path of students' autonomous learning, increases the resources for

students' autonomous learning, and promotes students' shift from "passive learning" to "active

learning". (Xiao Xiaoming, 2015)

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Shengnan, C., Jiansheng, H., Lei, D., Shuanghui, S., & Chao, W. (2024). Exploring Effective Paths for Artificial Intelligence to Empower Freshmen's

Autonomous English Learning in an “Internet Plus” Environment. Advances in Social Sciences Research Journal, 11(9). 261-280.

URL: http://dx.doi.org/10.14738/assrj.119.17641

SELF-DIRECTED LEARNING THEORY

Self-directed learning theories are largely derived from constructivism, which emphasizes the

constructive nature of the learning process and views personal development as knowledge and

experience.

The ability to learn on one's own is a necessary character and a key ability that students can

carry with them. Only with the ability of lifelong learning can we support future development

and adapt to the needs of lifelong development. Changchun Experimental Primary School

continues to explore the autonomous learning concept of teaching and learning mode research

practice path, build "a case of six learning" classroom teaching model "a case" refers to the

collective preparation of teachers to study the students' classroom learning guide list, six

learning A case" refers to the teachers' collective preparation and research of the students'

classroom learning guide, six learning "refers to the" guide, self-study, study, exhibition,

evaluation, practice learning "classroom teaching process, and language, math, English as a

breakthrough, the classroom as the main position, change the" Lecture Hall "for the" Hall

"learning". "Study Hall", aimed at cultivating students' autonomous learning ability and

improving learning efficiency (Wen Jian. 2024).

Self-directed learning, also known as learner autonomy, originated in the 1980s and was first

proposed by Henri Holec. Since then, many scholars have defined it, Holec (1981) defined it as

"the ability to take control of one's own learning". Then Cotteral (1999) gave a definition of self- directed learning, that is, self-directed learning is a process of self-control through self-planning

to achieve the learning goals. Dickinson defines it in terms of the basic characteristics of self- directed learners Dickinson defines self-directed learning in terms of the basic characteristics

of self-directed learners: the ability to understand the teaching objectives and teaching

methods, the ability to set their own learning goals, the ability to choose appropriate learning

strategies, the ability to monitor their own learning process, and the ability to evaluate their

own learning results (Dickinson, 1993). To summarize, autonomous learning is to want to

learn, to be able to learn, to know how to learn, to be good at learning, and to persevere in

learning (Ren Chunmei, 2010). Based on the above definition and self-management learning

theory.

And definitions of self-directed learning about foreign languages can be broadly categorized

into the following three groups:

Learning 1 is the "situational view" represented by L. Dickinson, which views self-directed

learning as a learning situation. In this context, the learner takes full responsibility for all

decisions related to his/her learning and the implementation of these decisions (Dickinson.

1987). The second is the "competence view", represented by Henri Holec, which defines self- directed learning as the ability to manage one's own learning. This ability is not innate, but

rather latent, and needs to be acquired through natural means or through formal learning in a

specialized system (Holec, 1981). The third is the "psychological view" represented by H.G.

Wolff, which believes that self-directed learning is a proactive act that must be carried out by

the learner to construct his/her own knowledge from the information he/she possesses (Wolff,

1952) It is similar to self-directed learning in that it mainly emphasizes the learner's primary

and the characteristics of autonomous learning are summarized below:

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Shengnan, C., Jiansheng, H., Lei, D., Shuanghui, S., & Chao, W. (2024). Exploring Effective Paths for Artificial Intelligence to Empower Freshmen's

Autonomous English Learning in an “Internet Plus” Environment. Advances in Social Sciences Research Journal, 11(9). 261-280.

URL: http://dx.doi.org/10.14738/assrj.119.17641

reduce the negative impact of acquired helplessness on them, and to enhance students' learning

effects (Wang Lirong, Hu Ni. 2023).

In the context of Internet plus, the current situation of freshmen's English learning has changed

significantly. First of all, the Internet provides abundant learning resources, such as language

learning applications (Duolingo, Memrise), online courses and grammar tools (Grammarly),

which enable students to personalize their learning according to their individual needs. This

diversity of resources improves the convenience and effectiveness of learning. Second, the

Internet has brought diverse learning methods, including MOOC and virtual classrooms, which

increase the flexibility and interactivity of learning and enable students to learn at different

times and places.

In addition, the Internet provides more opportunities for language practice. Students can

communicate with native English speakers through language exchange platforms (e.g. Tandem,

HelloTalk) to improve their speaking and listening skills. Meanwhile, online games, social

media and international forums also provide effective ways for language practice. Personalized

learning is enabled, with intelligent learning platforms recommending appropriate learning

content based on students' performance, thus improving learning efficiency.

However, Internet Plus also poses some challenges. The sheer volume and fragmentation of

information may lead to confusion in choosing what to learn, and over-reliance on Internet

resources may lead to reduced learning efficiency. In addition, distractions and time

management problems in the online environment may also affect learning outcomes.

Nevertheless, Internet Plus also facilitates socialization and cooperation among students, with

online discussions and study groups contributing to knowledge consolidation and teamwork.

In general, Internet plus provides freshmen with rich resources and diverse learning methods

for English learning, but they also need to deal with challenges such as information overload

and time management. By effectively utilizing Internet tools and resources, students can better

improve their English proficiency in the information age.

RESEARCH AND STUDIES

The scope of this survey is the freshmen of Beijing Institute of Petrochemical Technology,

students of various majors, using "Questionnaire Star" to distribute 510 questionnaires, 430

questionnaires were returned, of which 414 questionnaires were valid. The questionnaire was

designed with 16 questions, including the general situation of online English learning. The

questions are about the general situation of college students' English learning under the

influence of Internet plus, including: the problems of autonomous learning and the advantages

and difficulties of autonomous learning.

Correlation Analysis Using Kendall's tau-b

Correlation analysis is an analysis of the degree of correlation between two variables. There are

three ways of calculating correlation analysis which are Pearson's correlation coefficient (for

quantitative data and the data satisfies normal distribution), Spearman's correlation coefficient

(used when the data doesn't satisfy normal distribution), Kendall's tau -b correlation coefficient

(for ordinal fixed class variables). Therefore, we choose Kendall's tau -b correlation analysis.